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Motivated by the increasing number of drones used for package delivery, we first study the problem of Multiple drOne collaborative Routing dEsign (MORE) in this article. That is, given a fixed number of drones and customers, determining the delivery trip for drones under capacity constraint with stochastic demand for customers such that the overall expected traveling cost is minimized. To address the MORE problem, we first prove that MORE falls into the realm of the classical vehicle routing problem with stochastic demand and then propose an effective algorithm for MORE. Next, we have a scheme of resplitting customers into different individual delivery trips while the stochastic demands are determined. Moreover, we consider a variety of MORE, MORE-TW, and design an effective algorithm to address it. We conduct simulation experiments for MORE to verify our theoretical findings. The results show that our algorithm outperforms other comparison algorithms by at least 79.60%.

This paper expands previous work on stock-dependent demand for a retailer with a two-warehouse (OW/RW) situation to the case of deteriorating items and where the retailer seeks to obtain the integrated optimal distribution policy from collaboration with a supplier. Motivated by practical applications and recent literature, a policy is considered whereby products in good order from the retailer’s back-room (RW) are frequently transferred to its capacitated main store OW. Because the demand depends on the stock of good products in the OW, the aim is to keep this stock at its full capacity with products in good condition, and this can be done for as long as the RW stock of good products is positive. A firm’s objective function is the Net Present Value (NPV) of the firm’s future cash-flows. The profit functions are developed for both this continuous resupply policy and the commonly used policy in the OW/RW literature. Numerical examples are included and have been solved with grid search methods. The examples illustrate the benefits of adopting the continuous resupply policy, and also collaboration between the retailer and the wholesaler. Moreover, it is shown how these benefits can be shared by small adjustments to the product’s unit price between the firms.

Because of incomplete information on pre-sold products, consumers face uncertainty about the value of what they have purchased, which leads to a mismatch between supply and demand and a large number of returns. By developing appropriate return policies and effectively managing and handling consumer returns, retailers can not only reduce waste but also ensure better resource utilization, which is essential for sustainable development. In this paper, we analyze the full-refund and full-and-freight-refund policies of retailers and develop a game model based on binary competition for selecting the optimal return policy for the pre-sold products of two retailers. The study shows that when both retailers have low capacity, there is no pre-sale stage. However, when their combined capacity is high and exceeds the demand of non-strategic consumers, equilibrium depends on their combined capacity and the proportion of strategic consumers who choose to keep the pre-purchased product under both return policies. When the number of strategic consumers who retain pre-order products is low under the full-refund policy and both retailers have moderate capacity, equilibrium is achieved when an asymmetric return policy is followed rather than a symmetric return policy. Specifically, when the percentage of strategic consumers who keep their reserved products under the product return strategy is small and the capacity of the two retailers is moderate, the maximum benefit is achieved if one of the retailers adopts the policy of a full refund and the other adopts the policy of a full-and-freight refund. Otherwise, when one retailer adopts the policy of a full refund or a full-and-freight refund, its competitor should adopt the same strategy to gain maximum revenue. The research on retailers’ pre-sale and return strategies in this paper helps to optimize the operational strategies and operational processes of e-retailers, further improve the management and decision making of their joint pre-sale and return strategies, and help optimize retailers’ profits.

In this paper, a closed-loop supply chain (CLSC) consisting of one manufacturer and one supplier is considered. The capacity of the manufacturer is limited, the manufacturer can increase capacity by investing in capacity, and there are different cooperation contracts among the supply chain members. This paper pushes collecting activities upstream, assumes that the collecting activity can be completed by the supplier, and accepts that there is cooperation between the members, which increases supplier involvement. Dynamic game models among CLSC members are formulated. The optimal decisions of pricing, capacity investment, and collecting channels of the CLSC members are obtained, and the impacts of some important factors, for example, the capacity investment cost coefficient and the cost-sharing factors, on optimal decisions are investigated. The results reveal that the supplier collecting mode performs better in some scenarios, therefore, the management enlightenment desired by the supplier can be obtained. Additionally, the coordination between the manufacturer and the supplier sometimes fails to increase the closed-loop supply chain’s sustainability, which is a finding quite different from some current research results.

High-tech manufacturers frequently suffer from supply risk and capacity constraint. This paper considers a manufacturer who procures a type of high-tech component from two suppliers with asymmetric costs, capacities, and reliabilities, where the low-cost supplier has low reliability. One supplier is selected as a primary supplier and another as a backup supplier. The manufacturer places regular order to the primary supplier and determines backup order quantity from the backup supplier after random yield realization of the primary supplier. By developing a dynamic game-theoretical model, we obtain the optimal wholesale prices for the primary supplier and backup supplier, the optimal order quantity and supplier arrangement decisions for the manufacturer. We show that the manufacturer selects the low-cost supplier as a primary supplier and the high-cost supplier as a backup supplier (namely, LH policy) when the reliabilities of the two suppliers are close. When these reliabilities are not so close, the manufacturer chooses the high-cost supplier as a primary supplier and the low-cost supplier as a backup supplier (namely, HL policy). In addition, the manufacturer in the industry with scale diseconomies is more likely to select HL policy than that in the industry with scale economies. Compared with centralized decision making scheme, decentralized scheme induces the manufacturer more likely to select HL policy in the industry without scale economies, whereas in the industry with scale economies, decentralized scheme induces the manufacturer more likely to choose either HL policy when the capacity advantage of the low-cost supplier is weak, or LH policy when this advantage is significant.

Hub location problem is one of the new issues in location problems. This kind of location problem is widely used in transportation systems. In this paper, we investigate p-hub center location allocation problem under capacity constraint. The aim of the proposed model is to determine the location of hub nodes and the allocation of non-hub nodes to the hub in such a way that the maximum traveling time is minimized. In addition, since the problem is an NP hard problem, two metaheuristic algorithms including simulated annealing algorithm and ant colony are developed for solving large size real world problems. The performances of the proposed algorithms are examined via some numerical examples taken from known related benchmark sets (AP dataset). The best solutions found using metaheuristic algorithms are also compare to the results achieved using Lingo software. The results demonstrate that the proposed algorithms are able to find optimum or near optimum solutions in acceptable run times.

Given a directed graph with non-negative arc lengths, the Constrained Shortest Path Tour Problem ((Formula presented.)) is aimed at finding a shortest path from a single-origin to a single-destination, such that a sequence of disjoint and possibly different-sized node subsets are crossed in a given fixed order. Moreover, the optimal path must not include repeated arcs. In this paper, for the (Formula presented.) we propose a new mathematical model and a new efficient Branch & Bound method. Extensive computational experiments have been carried out on a significant set of test problems in order to evaluate empirically the performance of the proposed approach.

The load characteristic of typical household electrical equipment is elaborately analyzed. Considering the electric vehicles&rsquo, (EVs&rsquo, ) charging behavior and air conditioning&rsquo, s thermodynamic property, an electricity price-based demand response (DR) model and an incentive-based DR model for two kinds of typical high-power electrical equipment are proposed to obtain the load curve considering two different kinds of DR mechanisms. Afterwards, a load shedding strategy is introduced to improve the traditional reliability evaluation method for distribution networks, with the capacity constraints of tie lines taken into account. Subsequently, a reliability calculation method of distribution networks considering the shortage of power supply capacity and outages is presented. Finally, the Monte Carlo method is employed to calculate the reliability index of distribution networks with different load levels, and the impacts of different DR strategies on the reliability of distribution networks are analyzed. The results show that both DR strategies can improve the distribution system reliability.

By extending static traffic assignment with explicit capacity constraints, quasi-dynamic traffic assignment yields more realistic results while avoiding many disadvantages of dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models. We formulate requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We derive a new link travel time formula from vertical queuing theory that meets all requirements, unlike existing approaches in literature.

Istraživanje postojećih algoritama za rješavanje problema usmjeravanja vozila. Opisane Kohonenove neuronske mreže i algoritam K-sredina koji se koriste za rješavanje problema usmjeravanja vozila s grupiranim stanicama ograničenih kapacitetom. Generiranje novih instanci nad početnim negrupiranim stanicama i opis algoritma. Ispis rezultata, komentiranje rezultata i usporedba s rezultatima koje daje Google OR-tools biblioteka. Studied existing algorithms for solving vehicle routing problems. Described Kohonen neural netwok and K-means algorithm which are used for solving clustered capacitated vehicle routing problems. Generating new instances out of ungrouped cities and description of that generating algorithm. Printing and commenting results. Comparing results with Goolge OR-tools library results.

International audience; We investigate a variant of the Graph Partitioning Problem with capacity constraints imposed on the clusters, giving rise to quadratic constraints in 0–1 formulations. Several compact linearized models of the problem are proposed and analysed: (a) a model featuring binary variables which results from the application of the standard Fortet linearization technique; (b) a more compact model featuring only binary variables, obtained by linearization after reformulation of the quadratic constraints as bilinear constraints; (c) a strengthened version of the latter model, still featuring variables. Computational experiments comparing the relative strength and efficiency of the various models on a series of test instances involving complete graphs with up to 50 nodes are reported and discussed.

In this paper, we show that the "Merger Paradox" (Salant, Switzer and Reynolds, 1983) is mitigated when capacity constraint is considered. This is because outside firms who do not participate in a merger cannot expand their output beyond their existing capacity, and therefore, Stigler type of free riding is alleviated. When overcapacity is socially costly, it is also shown that a pro-merger fiscal policy may discourage ex ante capacity investment and hence alleviate overcapacity, if capacity building is not too costly. Furthermore, it can be shown that the optimal pro-merger subsidy is always welfare improving when it discourages capacity building.

Bus bridging has been widely used to connect stations affected by urban rail transit disruptions. This paper designs bus bridging routes for passengers in case of urban rail transit disruption. The types of urban rail transit disruption between Origin-Destination stations are summarized, and alternative bus bridging routes are listed. First, the feasible route generation method is established. Feasible routes for each pair of the disruption Origin-Destination stations include urban rail transit transfer, direct bus bridging, and indirect bus bridging. Then the feasible route generation model with the station capacity constraint is established. The k-short alternative routes are generated to form the bus bridging routes. Lastly, by considering the bus bridging resource constraints, the final bus bridging routes are obtained by merging and filtering the initial bridging routes. Numerical results of an illustrative network show that the bus bridging routes generated from the proposed model can significantly reduce travel delay of blocked passengers, and it is necessary to maintain the number of passengers in the urban rail transit below the station capacity threshold for ensuring a feasible routing design. One more important finding of this work is that the direct bridging route is preferred for short travel distances, while the indirect bridging route is preferred for longer travel distances. After the bridging bus routes are taken, the passenger&rsquo, s total travel time is significantly lower than when no measures are taken. However, after the capacity constraint of a station is considered, the passenger&rsquo, s total travel time will be increased by 3.49% compared with not considering a capacity constraint.

A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

Telsiz duyarga ağlar (TDA) üzerinde bulunan düğümlerin sahip oldukları enerji kaynakları genellikle sınırlıdır. Bu sebeple düğümlerin kullandıkları algoritmaların, enerji-etkin algoritmalar olarak tasarlanması önemlidir. Kapasite kısıtlı en küçük kapsayan ağaç (KEKA) algoritmaları, TDA üzerinde enerji etkin yönlendirme patikaları oluşturmak ve oluşturulan alt ağaçlar arasında yük dengesi sağlamak için kullanılabilir. Birçok merkezi algoritma bu problemi çözmek için tasarlanmış olmasına rağmen problemin TDA'ya uygun enerji-etkin çözümü bulunmamaktadır. Bu problemle ilgili merkezi bir algoritma; TDA'da n düğümlü ağ üzerindeki çıkış düğümünde uygulamanın bit karmaşıklığı O(n^2 log⁡n) bit olmaktadır. Bu çalışmada, TDA'da KEKA problemini çözmeyi hedefleyen iki algoritma önerilmiştir. DIST_PRIM (DPRIM) algoritmasını temel alan DCMST ve Esau-Williams (E-W) algoritmasını temel alan MCO algoritmalarının tasarımı verilmiştir. DCMST algoritmasının bit karmaşıklığı DIST_PRIM algoritmasıyla aynıdır, O(n^2)'dir. MCO algoritmasının bit karmaşıklığı O(n log⁡n) bit'tir. Önerilen DCMST algoritmasının performansı, DPRIM ve DCMST algoritmasının merkezi olarak çalıştırıldığı (CENTRAL) algoritmayla karşılaştırılmıştır. MCO algoritmasının performansı, E-W algoritmasının merkezi olarak TDA üzerinde çözülüp (CENTEW), çözümün tüm düğümlere bildirildiği senaryo ile karşılaştırılmıştır. Elde edilen simülasyon sonuçlarına göre DCMST ve MCO algoritmalarının enerji tüketimi açısından CENTRAL ve CENTEW algoritmalarına göre daha etkin olduğu görülmüştür., The devices, which are running on Wireless Sensor Networks (WSNs), generally have limited energy sources. Thus, makes foregrounding the design of "Energy-Aware" types of algorithms. Capacitated Minimum Spanning Tree (CMST) algorithms can be designed for finding energy-aware routing paths and for load-balancing among sub-trees connected to the sink device. Although, there are studies extensively in central settings there has not been any energy-efficient algorithm for the WSNs. The bit complexity of applying a central approach in the sink node is O(n^2 log⁡n) bits on a network having n nodes. In this study, we present the design of algorithms which aim to solve CMST problem in WSNs. DCMST is based on DIST_PRIM (DPRIM) algorithm and MCO is based on Esau-Williams (E-W) algorithm. The bit complexity of the proposed DCMST algorithm is O(n^2) bits and identical with DIST_PRIM. The bit complexity of the proposed MCO algorithm is O(n log⁡n) bits. We compare the performance of the proposed DCMST algorithm with DPRIM and central version of DCMST algorithm (CENTRAL). The performance of the proposed MCO algorithm with the straightforward implementation of E-W, where the problem is solved by the sink node and the result is sent to the other nodes (CENTEW) on WSN. According to the computational results, DPRIM and MCO algorithms are more efficient than CENTRAL and CENTEW algorithms with respect to the energy consumption.

In this thesis we aim at giving a general numerical framework to approximate solutions to optimal transport (OT) problems. The general idea is to introduce an entropic regularization of the initialproblems. The regularized problem corresponds to the minimization of a relative entropy with respect a given reference measure. Indeed, this is equivalent to find the projection of the joint coupling with respect the Kullback-Leibler divergence. This allows us to make use the Bregman/Dykstra’s algorithm and solve several variational problems related to OT. We are especially interested in solving multi-marginal optimal transport problems (MMOT) arising in Physics such as in Fluid Dynamics (e.g. incompressible Euler equations à la Brenier) and in Quantum Physics (e.g. Density Functional Theory). In these cases we show that the entropic regularization plays a more important role than a simple numerical stabilization. Moreover, we also give some important results concerning existence and characterization of optimal transport maps (e.g. fractal maps) for MMOT .; Dans cette thèse, notre but est de donner un cadre numérique général pour approcher les solutions des problèmes du transport optimal (TO). L’idée générale est d’introduire une régularisation entropique du problème initial. Le problème régularisé correspond à minimiser une entropie relative par rapport à une mesure de référence donnée. En effet, cela équivaut à trouver la projection d’un couplage par rapport à la divergence de Kullback-Leibler. Cela nous permet d’utiliser l’algorithme de Bregman/Dykstra et de résoudre plusieurs problèmes variationnels liés au TO. Nous nous intéressons particulièrement à la résolution des problèmes du transport optimal multi-marges (TOMM) qui apparaissent dans le cadre de la dynamique des fluides (équations d’Euler incompressible à la Brenier) et de la physique quantique (la théorie de fonctionnelle de la densité ). Dans ces cas, nous montrons que la régularisation entropique joue un rôle plus important que de la simple stabilisation numérique. De plus, nous donnons des résultats concernant l’existence des transports optimaux (par exemple des transports fractals) pour le problème TOMM.

This paper develops a multi-sector, small open economy Dynamic Stochastic General Equilibrium model, which includes the accumulation of human capital, built via public expenditures in education and health. Four possible fiscal rules are examined for total public investment in infrastructure, education, and health in the context of a sustainable resource fund: the spend-as-you-go, bird-in-hand spending; moderate front-loading, and permanent income hypothesis approaches. There are two dimensions to this exercise: the scaling effect, which describes the level of total investment, and the composition effect, which defines the structure of investment between infrastructure, education, and health. The model is applied to Kenya. For impacts on the non-resource economy, efficiency of spending, and sustainability of fiscal outcomes, the analysis finds that, although investment frontloading would bring high growth in the short term, the permanent income hypothesis approach is overall more desirable when fiscal sustainability concerns are taken into consideration. Finally, a balanced composition is the preferred structure of investment, given the permanent income hypothesis allocation of total investment over time.

Article history: Received 26 August 2010 Received in revised form 12 December 2010 Accepted 15 December 2010 Available online 15 December 2010 In this paper, a bi-objective mathematical model for emergency services location-allocation problem on a tree network considering maximum distance constraint is presented. The first objective function called centdian is a weighted mean of a minisum and a minimax criterion and the second one is a maximal covering criterion. For the solution of the bi-objective optimization problem, the problem is split in two sub problems: the selection of the best set of locations, and a demand assignment problem to evaluate each selection of locations. We propose a heuristic algorithm to characterize the efficient location point set on the network. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm. © 2011 Growing Science Ltd. All rights reserved.

This PhD dissertation addresses the foundations of a detailed characterisation of rail capacity constraints from an economic perspective.Traditionally, railway capacity has been studied from the standpoint of engineering in a monopolistic world where capacity choices were considered as an organisational issue and set out in internal procedures. However, there is now a growing interest in analysing this issue from an economic perspective, specially regarding the ongoing deregulation tendency.Firstly, the definition of railway capacity constraints is presented from an engineering perspective via timetable design, a key element in matching supply and demand for planned transport services. A better understanding of timetable construction methods led to highlighting the implicit trade-offs between the capacity supplied and service quality in terms of reliability in the current graphic timetable construction processes in European infrastructure managers. Secondly, this technical vision of the engineer is combined with the economic vision developed for other modes of transport. It allows us to formulate a microeconomic model of the consumer generalized cost function, specific to the railway services. This model highlights the dual effects for the users of a higher frequency of rail traffic. It impacts the expected scheduled delay cost (Mohring effect) on the one hand, and a congestion effect linked to the intensive use of the network on the other. Once the detailed generalised cost function for train users has been determined, we develop an equilibrium model, by considering users’ behavior, operators’ costs and by describing how supply and demand interact under different market conditions. We analyse the interactions between demand and supply and show that, under some conditions, it is optimal from a welfare point of view to charge the cost of capacity constraints in order to internalize the negative external effects generated, and send the right price signals to economic operators. Nevertheless, in certain cases, an additional frequency generates a positive externality (Mohring effect), thereby justifying a subsidy to encourage using the railway line rather than increases access charges., Cette thèse décrit de façon précise les éléments techniques et les fondements économiques qui permettent de caractériser la problématique de la contrainte de capacité ferroviaire dans son ensemble. Jusqu’à présent, la question de la contrainte de capacité ferroviaire a principalement été étudiée d’un point de vue ingénierie, dans un univers monopolistique où la répartition de la capacité et les ajustements en cas de conflit étaient gérés par des processus internes. Néanmoins, compte tenu d’une ouverture progressive à la concurrence du monde ferroviaire, analyser économiquement cette question devient un enjeu clé pour le gestionnaire d’infrastructure, dans un contexte de plus en plus régulé.Ce manuscrit aborde dans un premier temps, la définition de la contrainte de capacité selon la perspective de l’ingénieur, à travers la conception de l’horaire, un élément majeur de la rencontre entre l’offre et la demande pour les transports programmés. Une meilleure connaissance des méthodes de construction horaire a permis de mettre en évidence les arbitrages implicites entre la capacité offerte et la qualité de service en termes de fiabilité. La vision technique de l’ingénieur combinée à la vision économique développée dans les autres modes de transport, nous a permis d’élaborer dans un second temps, un modèle microéconomique du coût généralisé de l’usager, considérant les spécificités ferroviaires de la construction horaire. Cette modélisation a mis en évidence le double effet d’une fréquence ferroviaire supplémentaire, d’une part sur le coût de « deshorage » (effet Mohring) et d’autre part sur l’espérance du coût du retard, lié à un usage intensif du réseau. Une fois la fonction de coût généralisé spécifique au ferroviaire déterminée, nous avons construit un modèle d’équilibre offre-demande, en considérant le comportement des usagers ainsi que les coûts des opérateurs. Ce modèle décrit les interactions entre l’offre et la demande selon les différentes structures de marché. L’analyse développée démontre que sous certaines conditions, le régulateur peut être amené à valider une tarification de la contrainte de capacité, afin d’internaliser les effets externes générés et d’envoyer les bons signaux-prix aux agents économiques. Néanmoins, dans certains cas, une fréquence additionnelle génère une externalité positive (effet Mohring), justifiant ainsi une subvention pour intensifier l’usage de la ligne et non une tarification complémentaire.

Günümüzün rekabetçi ortamında bayilerin sürekliliklerini sağlayabilmek adına müşteri beklentilerini karşılayabilmesi gerekir. Kapasite limiti, bütçe, kayıp satış ihtimali ve talep görmeyen ürün stoğu gibi riskler nedeniyle ürün çeşitliliğini, derinliğini ve ürün stok miktarını belirlemek önemlidir. Bu tezde, sipariş üzerine üretim yapılan tek ve çoklu bayili sistemlerde, kapasite limiti altında ürün çeşitliliği planlaması problemi incelenmiştir. Çoklu bayili sistemlerde transfer-satış politikası da dikkate alınmıştır. Tek bayili sistemde olası müşteri davranışları; ziyaret edilen bayide aranan ürünün bulunması, bulunmaması durumunda olası bir diğer ürüne yönelmesi olabilir. Çoklu bayili sistemlerde ise, müşteri ziyaret edilen bayide aradığı ürünü bulabilir, bulamamsı durumunda ikame ürünü tercih edebilir, aranan ürünün başka bir bayide olması durumunda transfer-satış opsiyonu ile ürünü alabilir, ikame ürününün başka bir bayide olması durumunda da hem ikinci alternatife yönelme hem de transfer-satış gözlemlenebilir. Her iki sistem için bir diğer davranış da satış gerçekleşmeden müşterinin ayrılmasıdır.Problem toplam gelirin eniyilenmesi için kapasite limiti ile her noktada ürün çeşitliliğine karar vermek adına tanımlanmıştır. Tek bayili sistemde, ürünlerin kar marjları simetrik ise optimal çeşitliliğin populer küme (satın alınma olasılığı yüksek ürünlerden oluşur) içinde olduğu ve tüm kapasitenin kullanıldığı gösterilmiştir. Asimetrik kar marjlı ürünler için optimal çeşitlilik, ürünlerin satın alınma ihtimalleri ve kar marjları kullanılarak yorumlanmıştır. Çok bayili sistemlerde ürün çeşitliliği planlaması problemi kapasite limiti ve transfer-satış politikası dikkate alınarak çalışılmıştır. Bayilerin ortak ürün çeşitliliğinin ürünlerin kar marjları simetrik ise popüler küme içinde olduğu gösterilmiştir, ancak her bir bayi çeşitliliği popüler kümede olmayabilir ve kapasiteler kullanılmayabilir. Müşterinin ikame ürüne yönelimi, kapasite kullanımı ve ürün popülerliği arasındaki ilişki simetrik ve asimetrik kar marjlı ürünler için her iki sistemde de incelenmiştir. Elde edilen özelliklerden yararlanılarak sezgisel bir algoritma geliştirilmiş ve sayısal analizler ile bu algoritmanın performansı ölçülmüştür.Anahtar Kelimeler: Harici Talep Modeli, ˙Ikame Ur¨un, Kapasite Limiti, Transfer- ¨Satı¸s, Ur¨un C¸ e¸sitlili˘gi Planlaması To survive in today's competitive market, firms need to meet customer expectations by offering high quality products with high variety. However, there might be some physical and financial constraints limiting the assortment size. The process of finding the optimal product assortment by considering both the benefits of a large assortment as well as the costs and limits of it is known as assortment planning. In this thesis, assortment planning is analyzed under predetermined assortment capacitylimits for two cases. First, a single firm's optimal assortment problem is studied to maximize its profits. Second, assortment planning problem of a system of multiple rms is investigated jointly, where firms are interacting through product sharing, called transshipments. Transshipments are known to increase product availability, thus decreasing stock-outs. Transshipments have been always utilizedas an emergency demand satisfaction action in support of inventory management inthe literature. Dierently, in this study, transshipments are evaluated in advanceof inventory management while making the assortment planning of rms. In bothproblems, demand is dened to have an exogenous model, where each customer hasa predetermined preference for each product from the potential set. Proportionaldemand substitutions are also allowed from an out of assortment product to others.The results on the optimal assortment of a single rm are used as a benchmark tothe optimal assortments of multiple rms communicating through transshipments.By relying on proven optimality results, it is shown how easily optimal assortmentscan be obtained compared to a full enumeration. Extensive numerical analyses arereported on the performances of the heuristic algorithm and sensitivity of optimalassortments to system parameters.Keywords: Assortment Planning, Capacity Constraint, Exogenous Demand Model,Substitution, Transshipment. 97

We present evidence that binding mortgage processing capacity constraints reduce mortgage originations to borrowers with low to modest credit scores. Mortgage processing capacity constraints typically bind when the demand for mortgage refinancing shifts outward, usually because of lower mortgage rates. As a result, high capacity utilization leads mortgage lenders to ration mortgage credit, completing mortgages that require less underwriting resources, and are thus less costly, to produce. This is hypothesized to have a particularly adverse impact on relatively higher credit‐risk borrowers’ ability to obtain mortgages. What is more, we show that, by lowering capacity utilization, a rise in interest rates can, under certain circumstances, induce an increase in mortgage originations to relatively higher risk borrowers. In particular, we find fairly large effects for purchasing borrowers with low to modest credit scores, in which we find that a decrease in capacity utilization of 4 applications per mortgage employee (similar to that observed from 2012 to 2013) could result in increased purchase mortgage originations, as the relaxed capacity constraint might have offset any negative effect on mortgage demand from higher interest rates.

Most balancing markets of electric power are organized as uniform-price auctions. In 2001, the balancing market of England and Wales switched to a pay-as-bid auction with the intention of reducing wholesale electricity prices. Numerical simulations of an electricity auction model have indicated that this should lead to decreased average prices. In this work we prove two inequalities which give an analytic proof of this claim in the same model.

We adopt a game theoretic framework to model key features of agricultural procurement markets in order to explore the interaction between capacity constraints and spatial competition and the implications for input pricing by processing plants. A key finding is that the Lofgren’s (1986) equivalence between uniform delivery and FOB pricing for profit-maximizing firms extends to a capacity-constrained monopsonist. Our results also show that the relative dominance of alternative pricing strategies and the efficacy of capacity constraints as a collusion mechanism is not impervious to market structure asymmetries. When plants can procure inputs from areas with different market structures, capacity constraints greatly influence the optimal pricing strategy, the total surplus, and the fraction of such surplus appropriated by processing firms. In particular, when operating under binding constraints, firms “escape” competition by procuring more inputs from less competitive areas, while still benefiting from the “collusion-like” benefits of fixed output. Therefore binding constraints and asymmetric market structures reinforce each other to increase the fraction of total surplus appropriated by processing firms.

The seasonal variability of production shrinks during a boom, not only at the industry level, but also at the plant level. Since this relationship is significant especially among plants with high capacity utilization, our finding is consistent with the capacity constraint hypothesis.

International audience; This paper analyzes price competition in the case of two firms operating under constant returns to scale with more than one production factor. Factors are chosen sequentially in a two-stage game generating a soft capacity constraint and implying a convex short-term cost function in the second stage of the game. We show that tacit collusion is the only predictable result of the whole game, that is, the unique payoff-dominant pure strategy Nash equilibrium. Technically, this paper bridges the capacity constraint literature on price competition and that of the convex cost function.

In this paper, we investigate the effects of different fleet compositions on travel demand in the case of metro system breakdowns (such as reductions in train performance or unavailability of a rail convoy or a track section), in order to provide a Decision Support System (DSS) which allows the decision-maker to estimate the increase in travel and waiting times of passengers, and thus identify the optimal intervention strategy to adopt so as to minimise their discomfort. In particular, we adopt a micro-simulation model of the metro system to estimate the behaviour of passengers waiting on the platform and apply the proposed methodology in the case of a real-dimension network.

İşletmeler birden fazla farklı amaçlar için kurulabilmektedir. Ancak bu kuruluş yatırımları sermaye gerektirmektedir. Sermayenin fırsat maliyeti olmakla birlikte risk söz konusudur. Bu nedenle işletmelerin vazgeçilemeyecek temel kuruluş amaçlarından birisi kar elde etmektir. İktisadi hayatlarını devam ettirebilmeleri içinde karlılıklarında sürekliliği sağlamaları gerekmektedir. İşletmeler kar elde etmek ve bu karlılığın sürdürülebilir olmasını sağlamak için kaynaklarını etkin ve verimli kullanmalıdır. İşletmelerin sahip olduğu kaynaklar işletmenin mal ve hizmet üretme kapasitelerini belirler. Başka bir açıdan bakıldığında ise işletme kapasitesi, işletmenin değer yaratma potansiyelidir. Ancak bu potansiyelin ne kadarının fiiliyata dönüştürülebileceği teknik, operasyonel, yönetsel süreçlerinin doğru işlemesi, verimliliği ve yönlendirilmesi ile ilgilidir.İşletmeler ancak kapasiteleri ölçüsünde üretim ve rekabet yapabilirler. Bu nedenle kapasiteleri doğrultusunda satış yapabilir, nakit üretebilir ve kar elde edebilirler. İşletmelerin kapasitelerini etkin bir şekilde kullanabilmeleri gerekmektedir. Bunun içinde; işletmelerin kurulurken kapasite ihtiyacını doğru öngörmeleri ve bu doğrultuda yatırım planlaması yapmaları gerekmektedir. Faaliyete geçtiğinde ise kapasitelerine etki eden faktörleri iyi analiz ederek, işletmenin dinamiklerine uygun bir kapasite yönetiminin sağlanması gerekmektedir. Bir işletmenin kapasitesi sadece makine ve teçhizatın üretim kabiliyeti ile hesaplanamaz. İşletmelerin üretim kabiliyeti tüm üretim faktörlerinin uyumu ve verimi ile doğru orantılıdır. Kapasite işletmenin sermaye maliyetini ifade etmektedir. Bu nedenle atıl kapasite; işletmenin kapital gücünü atıl bir şekilde tutması ve ekonomideki kayıp olarak değerlendirilebilir. Yetersiz kapasite ise; işletmenin yerine getiremeyeceği taahhütler altına girmesi, nihayetinde itibar kaybı ve belli cezai müeyyideler ile karşılaşma riski, bunun doğal sonucu olarak da müşteri ve sipariş kaybı olarak görülebilir. Bu nedenle işletmelerin üretim kapasitelerini doğru bir şekilde hesaplayabilmeleri, farklı ürün bileşenlerinde kapasitesinin nasıl değiştiğini önceden görüyor olmaları, makine ve teçhizat dışında kapasitesine etki eden unsurları iyi gözlemlemesi gerekmektedir. Bunun doğal bir sonucu olarak işletmelerin kapasitelerinin etkin kullanımı için kritik performans göstergelerini oluşturmaları ve bunları anlık takip edebiliyor olmaları gerekmektedir.İşletmelerin stratejik planları yapılırken de kapasite düzeyine uygun planlama yapılması gerekmekte olup, stratejisi ile uyumlu kapasite yatırım planlamasını da yapması gerekmektedir.Günümüzde rekabet küresel ölçekte yaşanmakta olup, firmaların iktisadi hayatlarını idame ettirebilmek için rekabetçi olmaları zorunlu hale gelmiştir. Ülkemiz dâhil gelişmiş tüm ekonomilerde rekabetçi ortamın korunması devlet tarafından güvence altına alınmaktadır. İşletmelerin rekabetçi ortama ayak uydurabilmeleri için 3 hususta sürekli gelişmeleri gerekmektedir. Bunlar; Hız (müşteriye zamanında geri dönüş, temrine uyum vb.), Kalite (İstenilen standartlarda ürün üretilmesi), Maliyet Liderliği (Emsallerine göre daha uygun maliyet) şeklinde sınıflandırmak mümkündür. Doğru bir kapasite yönetimi işletmeleri özellikle hız ve maliyet liderliği konularında avantajlı hale getirecektir. Kapasitenin doğru yönetilebilmesi içinde tüm süreçlerin verimli ve etkin çalışması, iş sonuçlarının düzenli ölçülerek analiz edilmesi ve iyileştirilebilir yanların tespit edilerek geliştirilmesi, işletmelerin gelişmesi ve iktisadi hayatlarının devamlılığı için kritik öneme sahiptir. The organizations can be set up for several different purposes. However, these organizations require capital investment. Although there is a risk for the opportunity cost of capital. Accordingly, one of the indispensable foundation goal for the organization is to obtain any profit. Businesses should use the resources to make a profit and to ensure that effective and efficient sustainable profitability. Resources owned by the business determines the company's capacity to produce goods and services. When another perspective, operational capacity, creating the potential value of the business on. But how much of this potential can be converted into deeds technical, operational, the correct functioning of the administrative process is concerned with efficiency and guidance.Businesses are able to produce, but the extent of capacity and competition. Therefore, in accordance with the capacity to make sales, generate cash and profits they can get. Businesses should be able to use their capabilities effectively. In it; predict capacity needs while establishing their businesses are required to make accurate and investment planning in this direction. When put into operation by analyzing the factors that affect the capacity of good, it is necessary to ensure the proper operation of the dynamic capacity management. Calculated only with the production capacity of a company's ability to machinery and equipment. Production capability of the business is directly proportional to the adaptation and productivity of all factors of production. Capacity refers to the capital cost of the business. Therefore idle capacity; keep the capital strength of the business disposed of in a manner considered as lost and the economy. If there is insufficient capacity; to come under the company can not fulfill commitments, loss of reputation and ultimately the risk of confrontation with certain criminal sanctions, as it can be seen as a natural consequence as the loss of customers and orders. Therefore, enterprises can accurately calculate production capacity, he sees how they are changing the capacity of the different product components in advance, the factors affecting the capacity except machinery and equipment should be well observed. The creation of key performance indicators for effective use of the capacity of the business as a natural consequence and should be able to follow them instantly.Strategic plans of the business is to be done is being done according to the capacity planning level, it is necessary to make the investment planning capacity compatible with the strategy.Today, competition is taking place on a global scale, it has become necessary to be competitive in order to sustain economic life of the company. The competitive environment in developed economies, including the protection of all our country is guaranteed by the state. Businesses must continuously improve in three aspects in order to keep pace with the competitive environment. they are; Speed (return on time to the customer, expediting the compliance etc.), Quality (products manufactured in the desired standard), Cost Leadership (more cost effective compared to peers) can be classified as. Towards a capacity management company will make particularly advantageous speed and cost leadership in their fields. Efficient and effective operation of the whole process can be managed correctly in capacity, improving the analysis and identification of regularly measuring the business results and improved as well, for the continuity of the business of life and economic development is of critical importance. 104

The management of public transport for rebalancing the use of transportation systems is a useful tool for reducing negative externalities without excessively affecting zone accessibility. In this context, a rail or metro system can be a key element for producing a high-quality supply of public transport. Obviously, due to the great vulnerability of rail technology to system failures, it is necessary to develop suitable tools to identify rapidly, even with off-line procedures, the best operational strategies which minimise user discomfort produced by such failures. Hence, the authors proposal is to extend previous models proposed in the literature by considering travel demand as an outcome of a random variable and not only in terms of average values. The proposed approach is applied in the case of a real dimension metro network, considering a wider class of failure contexts.

International audience; Due to environmental issues, electric mobility is one of the mobility alternatives that are receiving a huge attention nowadays. In fact, in the last few years electric vehicles have entered the world's car market. This revolutionary technology requires a fast deployment of electric charging stations since the key issue in this system is recharging the batteries. In this work, we propose an optimized algorithm to locate electric-vehicles charging stations. Different factors and limitations are considered and a real case study is given as an application. We first determine the appropriate strict constraints and cost of charging stations' location; and then we propose a mathematical formulation of the problem before solving it using our optimized algorithm named OLoCs (Optimized Location Scheme for electric charging stations). This latter is a heuristic solution; in which we adapt a genetic algorithm to solve the charging stations' location problem. We add a new operator to the classical genetic algorithm to prevent premature convergence and improve the efficiency of the algorithm. OLoCs determines the necessary number of charging stations and their best opening placement. Finally, we evaluate OLoCs performances by analyzing its convergence time and depicting the graphic placement results on a studied map.

In this paper, we propose an off-line procedure for determining the optimal operational strategy in the case of rail and/or metro system failure. The procedure is based on a micro-simulation approach for estimating effects of each feasible intervention strategy on travel demand. Numerical results in the case of a real-size metro network show that optimal solutions could differ according to travel demand levels and/or breakdown severities.

Swiss Confederation Ukraine has extensive public infrastructure inherited from the Soviet times but much of it has fallen into disrepair over the past decades and needs major rehabilitation or replacement so that growth may continue. Creating fiscal space for investing more is one of the critical tasks that facing the country, but a constrained fiscal space together with the use of investments as a stimulus for growth call for more efficiency in public investment management practices. There are a number of fundamental issues that need to be addressed if Ukraine is to make progress in its reform ambitions for public investment management (PIM). The most significant are: (1) most projects avoid scrutiny due to loopholes in classification (lack of definition of a public investment project); (2) there is no effective economic appraisal and appraisal review procedures in place due to limited human resource (HR) capacity, and no common technical standards; (3) the PIM system does not seem to block new projects from entering the budget but allows ministries to delay ongoing ones and squeeze in new ones; and (4) lack of strategic guidance with which to prioritize complicates project selection. One of the fundamental building blocks of a sound PIM system is a clear, legal definition of what counts as a public investment project and what does not. It should be pointed out that this already high discrepancy is only a comparative measure of input values. Developing projects that are output and performance driven should yield even greater efficiencies. Between 2000 and 2008, Ukraine was an average growth performer in a fast growing region, with gross domestic product (GDP) growth averaging 7 percent. As the global financial crisis hit the Ukrainian economy it contracted by 15 percent in 2009, exposing its underlying macroeconomic and structural vulnerabilities. As a result of the insufficient structural transformation and impact of the economic crisis, Ukraine now faces substantial fiscal pressures that threaten economic stability and growth. The Government of Ukraine recognized the need for a modern public financial management (PFM) system and put considerable emphasis on several aspects of PFM reforms. Training for the development of capacity in the PIM system is tricky in Ukraine. It is becoming clear that due to the dynamic nature of the Ukrainian civil service, officials are rapidly moving from one area of the Administration to another.

Distributed Computing Systems (DCS) have become a major trend in computer system design today, because of their high speed and reliable performance. Reliability is an important performance parameter in DCS design. In the reliability analysis of a DCS, the term of K-Node Reliability (KNR) is defined as the probability that all nodes in K (a subset of all processing elements) are connected.In this paper, we propose a simple, easily programmed heuristic method for obtaining the optimal design of a DCS in terms of maximizing reliability subject to a capacity constraint. The first part of this paper presents a heuristic algorithm which selects an optimal set of K-nodes that maximizes the KNR in a DCS subject to the capacity constraint. The second part of the paper describes a new approach that uses a K-tree disjoint reduction method to speed up the KNR evaluation. Compared with existing algorithms on various DCS topologies, the proposed algorithm finds a suboptimal design much more efficiently in terms of both execution time and space than an exact and exhaustive method for a large DCS.

In this paper we consider an oligopolistic market in which one firm can be monopolist on her residual demand function and derive implications on the shape of her profit function, which we show may not be concave in price. We propose a simple price-capping rule that induce the pivotal operator to compete for quantity instead of taking advantage of her monopoly. Then, we analyze the bidding behaviour of the dominant electricity producer operating in the Italian wholesale power market (IPEX). This firm is vertically integrated and in many instances she acts as a monopolist on the residual demand. We find that, contrary to expectations, this pivotal firm refrains to exploit totally her unilateral market power and, therefore, bids at levels well below the cap. We discuss such a behaviour and derive implications for the setting of the price cap.

In urban contexts, the adoption of policies to promote the use of public transport systems represents a useful tool for decision-makers to reduce the environmental impact of private car use. Especially in high-density contexts most travel demand can be satisfied efficiently by means of high-quality rail systems. However, in the event of breakdowns, since faulty trains cannot usually be overtaken and their removal could pose extreme difficulties especially in metropolitan systems with two separate tunnels, re-establishing the regular service could involve inconveniently long travel times. Hence emergency management has to take into account effects on travel demand. In this framework, we analyse such effects for different levels of degraded services in order to define the best strategy to adopt to minimise user discomfort. We extend ideas proposed elsewhere in the literature by introducing capacity constraints of rail vehicles in order to provide more realistic simulated effects. Finally, we describe the application of the proposed approach in the case of the Naples metro system.

International audience; This article presents a model of private vertical contracting with a capacity constrained monopolistic supplier. I consider 'full capacity beliefs' that are consistent with an upstream capacity constraint and are 'wary' when the constraint is tight or production is costless. I show that, facing a capacity constraint, the supplier may preserve its monopoly power in equilibrium. This result stands in sharp contrast to the standard result that the supplier cannot preserve its monopoly power, which holds under the usual implicit assumption of an infinite production capacity.

International audience; This paper explores the impacts of Protected Designation of Origin (PDO) certification on the costs and profits of firms as well as consumers’ and total welfare. The paper argues that PDO labels are different from other common labeling schemes, as they involve technological and capacity constraints that influence their economic efficiency. Using a theoretical model of endogenous quality choice,which incorporates vertical differentiation with the costs constraints linked to the PDO label, we explore the way producers can signal their quality either by certifying their product through PDO or by investing in a collective private common label. Results show that even if PDOs are efficient from a producer perspective, a society might be better off with less stringent techniques of quality signaling, relying on private collective certification.

This paper analyses the competitive effects of capital requirement regulation on an oligopolistic credit market. In the first stage, banks choose the structure of refinancing their assets, thereby making an imperfect commitment to a loan capacity as a function of the chosen degree of capitalization and the regulatory capital requirement. In the second stage, loan price competition takes place. It is shown that a capital requirement regulation may not only decrease the supply of credit through an increased marginal cost effect but can have an additional collusive enhancing effect resulting in even higher credit prices and increased profits for the banks., Working papers series, ISSN 2628-1724, 2010, Heft 12

16 pages; International audience; In network assignment models of urban transit, traffic congestion has been modelled either as vehicle congestion along the route track, or by reducing the service frequency with respect to excess flow of passenger arrivals. A third type of congestion has been modelled by Leurent (1), (2): that of seat congestion, because being seated or standing make distinct on-board states for a transit rider, resulting in distinct discomfort costs, with potential influence on route choice on the transit network. The paper has a twofold objective of, first, providing a concise statement of the seat congestion model, and second, reporting on its application to the Paris metropolitan area – a problem of very large size. The model makes explicit the residual set capacity and its evolution at any stage along a service line; the priority rules amongst riders depending on their order of arrival in the competition to get a seat; and the randomness in leg cost to the rider. Line algorithms and consistent network algorithms are provided.

The article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed., 17 pages, 4 figures, 2 tables, journal

Voronoi tessellations specify a partition of a given space according to a set of sites where all points in that space are assigned to the closest site. Capacity-constrained Voronoi tessellations are special cases of Voronoi tessellations in which the region of each site has a predefined area. For example, the capacity constraint could state that each region in a Voronoi tessellation must have the same area, or it could state that all regions have individually defined areas. Thus, the capacity constraint allows us to control the spatial influence of the sites in the tessellation.Unfortunately, there exists no straightforward approach for computing capacity-constrained Voronoi tessellations. Rather, they have to be generated with iterative optimization techniques. In this thesis, we present three different approaches for the computation of capacity-constrained Voronoi tessellations. The algorithms are tailored for either continuous or discrete spaces, and allow us to employ different distance functions that result in Voronoi tessellations with different characteristics. The presented continuous space algorithms modify the locations and weights of the sites, thereby reducing the error between the current and the desired areas of the regions. Although a proof of convergence is still an open research problem, our experiments showed their reliable convergence towards arbitrarily precise capacity-constrained Voronoi tessellations. In contrast, our discrete space algorithm starts with an arbitrary assignment of the points in the discrete space to the sites that fulfills the capacity constraint. This assignment is then optimized until it achieves an equilibrium state that represents a valid Voronoi tessellation. The convergence of the algorithm to such an equilibrium state is guaranteed.Based on these three algorithms, we present two applications that utilize capacity-constrained Voronoi tessellations. The first application are \emph{Voronoi treemaps} for the visualization of attributed hierarchies in the domain of information visualization. This application focuses on the resulting polygonal regions of the Voronoi tessellations. The second application are capacity-constrained point distributions as a general purpose method for sampling-related tasks in the domain of computer graphics. This application focuses not on the tessellations itself but on the resulting distributions of sites. Both applications represent significant advances in their field with respect to the flexibility of the method and the quality of their results.

Today's highly competitive business environment forces supply chain managers to maintain high service levels while keeping inventory-related costs as low as possible. Therefore, placing the right amount of safety stock at the right places in the supply chain is an important aspect of effective inventory management. This safety stock placement problem, for which some solution strategies have been proposed in the case of uncapacitated supply chains, becomes much more complicated when, in addition to the variability of the demand, capacity constraints also come into play. In this paper we propose a model to locate safety stocks in a capacitated supply chain with the objective of maintaining the required service level. The underlying relationships linking excess capacity, demand variability, and service levels are analysed to gain deeper understanding of the safety stock placement problem in capacitated supply chains. Based on these relationships a solution approach for the problem is proposed and is tested with Monte Carlo simulation

In Tuve outside of Gothenburg one of Volvo Trucks’ factories for final assembly is located. In the same plant the Frame factory is located, manufacturing frame sides for the Tuve assembly lines, as well as other foreign plants. Companies in the heavy trucks market have been operating in high capacity utilization for several years and the Frame factory at the Tuve plant is no exception. Customer demand is exceeding current production rate at the Tuve Frame factory and volume increases have been incremental since last major reconstruction in 2005. Shifting bottlenecks are a major issue at the Frame factory and an investigation of the production line and the planning process is requested to detect possibilities for capacity increases without major investments in new machines. The purpose of the thesis is to investigate Volvo Trucks’ frame side production line and give recommendations for controlling order releases and increasing line capacity. The goals are to define the current state of the production line and its’ constraints, develop an order release method, and to build a simulation model for testing of order release methods and examining constraint behavior. The authors examined the production line with first hand observations of the process flow and work methods. Logging statistics, process documents, time studies and interviews with personnel at the Frame factory were used as input for the empirical description, constraint analysis and simulation testing. A tool for analysis and experiments was discrete event process simulation in AutoMod™. The current state of the Frame factory is a high volume general flow shop with small buffer stocks and closely arranged resources similar to lines described under the Just-in-time ideology. Highest utilization is found in two early stations for punching and plasma cutting. The Overall Equipment Effectiveness (OEE) is close to 60 percent in both stations which show high levels of down time and speed losses. Product types with varying operating times in Capacity Constraint Resources (CCR) create shifting bottlenecks unless scheduling of order releases is leveled. Since buffers are small in the Frame factory, unleveled scheduling will risk starving or blocking CCRs which reduces throughput. Recommendations are to focus on the punching machines and the plasma cutter as bottlenecks. According to Theory of Constraints, concentrating on other resources will not increase throughput but could reduce lead time and WIP. A short setup time in the Rollformer is critical to avoid starving the punching machines. Keeping the Punching buffer stocks filled before the setup begins allows setup time variations without decreasing throughput. The largest contributor to differences in lead time, WIP and throughput is high variations in availability in CCRs. The current manual logging of machine losses cannot account for all losses at current rate and recommendations are to install automatic logging in CCRs. The product mix should be monitored to maintain a leveled workload in resources to avoid the shifting bottleneck phenomenon. Releasing orders with consideration of short term loading in CCRs gives small increases in throughput of the production line. Validerat; 20101217 (root)

A Voronoi diagram of a set of n sites partitions a finite set of m points into regions of different areas, called the capacities of the sites. In this paper we are interested in Voronoi diagrams in which the capacities are given as constraints. We compute such capacity-constrained Voronoi diagrams in finite spaces by starting with an arbitrary partition that fulfills the capacity constraint without representing a valid Voronoi diagram. We then iteratively swap the assignment of points to sites guided by an energy minimization that is related to the distance function of the Voronoi diagram. This optimization converges towards a valid Voronoi diagram that fulfills the capacity constraint due to the restriction to swap operations. The straightforward structure of our algorithm makes it easy to implement and flexible. The computational time complexity for each iteration step is O(n2+nmlog m/n). We provide examples for extensions of our algorithm such as applying different energy functions, or generating Voronoi diagrams with centroidal and/or void regions.

In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applications to computer resource sharing. First of all, we prove that networks of symmetric queues with Jackson or Kelly routing are both insensitive to the service requirement distribution even if at arrivals, departures or migration events, customers at each queue are randomly permuted according to some law that may depend on the network state. We also identify some non-symmetric service disciplines for which the insensitivity property holds. We then propose two new throughput metrics for data networks. We prove some generic properties satisfied by these two metrics and we illustrate their difference through some examples. Finally, we prove that balancing elastic traffic sources worsens performance in terms of throughput and, in the presence of admission control, of blocking probability., Nous abordons dans cette thèse le problème de l'insensibilité dans les réseaux de files d'attente et quelques applications au partage de ressources informatiques. Tout d'abord, nous montrons que les réseaux de files d'attente symétriques avec le routage de Jackson ou de Kelly sont tous insensibles à la distribution des demandes de service même si à l'arrivée, au départ ou au changement de files d'un client quelconque, les autres clients dans chaque file sont permutés au hasard selon certaine loi dépendante de l'état du réseau. Nous identifions également certaines disciplines de service non symétriques pour lesquellesla propriété d'insensibilité est satisfaite. Ensuite, nous proposons deux nouvelles métriques de débit pour les réseaux de données. Nous montrons quelques propriétés génériques satisfaites par ces deux métriques et nous illustrons leur différence à travers quelques exemples. Enfin, nous montrons que l'équilibrage de sources de trafic élastique détériore la performance en termes de débit, et en présence de contrôle d'admission, de probabilité de blocage.

The issue of safety stock placement is one of the challenging problems in the area of supply chain design. Safety stocks play a significant role in supply chains since they assure the service level and the smoothness of the flow of materials throughout the chain. Some special models of the problem have been solved efficiently, especially in the case of uncapacitated serial or tree chains. This paper discusses some existing models and their limitations. Computer experiments are used to identify possible solution strategies for safety stock placement problem for capacitated serial chains.

The issue of safety stock placement is one of the challenging problems in the area of supply chain design. Safety stocks play a significant role in supply chains since they assure the service level and the smoothness of the flow of materials throughout the chain. Some special models of the problem have been solved efficiently, especially in the case of uncapacitated serial or tree chains. This paper discusses some existing models and their limitations. Computer experiments are used to identify possible solution strategies for safety stock placement problem for capacitated serial chains.

In a real-time electric power auction, the bids of producers consist of committed supply as a function of price. The bids are submitted under uncertainty, before the demand by the Independent System Operator has been realized. In the Supply Function Equilibrium (SFE), every producer chooses the supply function maximizing his expected profit given his residual demand. I consider a uniform-price auction with a reservation price, where demand is inelastic and exceed the market capacity with a positive probability, and firms have identical constant marginal costs but asymmetric capacities. I show that under these conditions, there is a unique SFE, which is piece-wise symmetric.

Producers submit offer curves to a procurement auction, e.g. an electricity auction, before uncertain demand has been realised. In the supply function equilibrium (SFE), every firm commits to the offer curve that maximises its expected profit, given the offer curves of competitors. The equilibrium is given by a system of differential equations. In practice, it has been very difficult to find valid SFE, i.e. non-decreasing solutions, from this system, especially for asymmetric producers. This paper shows that valid SFE can be calculated by means of a shooting algorithm that combines numerical integration with an optimisation procedure that searches for an end-condition. Multiple/parallel shooting is used for ill-conditioned cases.

Producers submit committed supply functions to a procurement auction, e.g. an electricity auction, before the uncertain demand has been realized. In the Supply Function Equilibrium(SFE), every firm chooses the bid maximizing his expected profit given the bids of the competitors. In case of asymmetric producers with general cost functions, previous work has shown that it is very difficult to find valid SFE. This paper presents a new numerical procedure that can solve the problem. It comprises numerical integration and an optimization algorithm that searches an end-condition. The procedure is illustrated by an example with three asymmetric firms.

In a real-time electric power auction, the bids of producers consist of committed supply as a function of price. The bids are submitted under uncertainty, before the demand by the Independent System Operator has been realized. In the Supply Function Equilibrium (SFE), every producer chooses the supply function maximizing his expected profit given his residual demand. I consider a uniform-price auction with a reservation price, where demand is inelastic and exceed the market capacity with a positive probability, and firms have identical constant marginal costs but asymmetric capacities. I show that under these conditions, there is a unique SFE, which is piece-wise symmetric.