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Multiple factors contribute to the occurrences of disruptions in workflow management within the e-commerce system that focuses on the distribution of goods and other fast-moving consumer goods (FMCG). These disruptions have particularly affected and increased lead times and caused frequent shipment delays. The causes of these disruptions, especially in the context of distribution of goods and FMCG towards inventory control, have been widely speculated upon in recent years. Given the recent interruptions, the study presented in this paper used a methodology called statistical model analysis (SMA) to study the impact of human factors (HFs) on the system performance in a warehouse distribution system. A case study was taken on a particular company called ABC and XYZ to model the impact of some specific HF such as job fatigue, and job rotation to name a few and to uncover the underlying reasons behind the ongoing disruptions within the distribution system. Specifically, the result of this study aims to provide a data-driven understanding of these issues and one of the contributions of this study is to enhance our understanding of the significance of these HFs, rather than focusing on the equipment and materials as seen in prior research. Through this data-based approach study, stakeholders in operations management, e-commerce, and the supply chain system would be well-informed in many ways to resolve the challenges faced by humans in the system towards enhancing their overall system performance. [ABSTRACT FROM AUTHOR]

The paper examines the perspectives of linear-quadratic (LQ) optimal control in steering the process of goods distribution in logistic systems with multiple transportation options. In the considered class, the distribution centre governs the stock replenishment process of subordinate depots, from which un uncertain market demand is served. The centre is linked with the depots via shared supply channels with different characteristics regarding delay, reliability, and capacity, e.g. train vs truck delivery. The design objective is a rule of dynamical channel allocation – how many goods to send in a period using a given mode – so that balanced, cost-efficient system performance and high customer service rate are achieved. The received goods are inspected for quality defects and rejected when faulty. Thus, one needs to cope with two major sources of uncertainty: unpredictable demand variations and channel imperfections. A multi-variable LQ optimal controller is designed and presented in closed form for detailed analytical and numerical treatment. It is formally shown that despite perturbations, the controller always establishes a non-negative and upper-bounded replenishment signal, and the stock level does not cross the reference value. Conditions for warehouse space selection and obtaining full demand satisfaction at the depots are specified and formally proved. [ABSTRACT FROM AUTHOR]

This paper investigates strategies for improving supply chain delivery timeliness when the delivery time follows an asymmetric Laplace distribution. Delivery performance is measured using a cost-based analytical model which evaluates the expected cost for early and late delivery. This paper presents a set of propositions that define the effect of changes to the parameters of the delivery time distribution on the expected penalty cost for untimely delivery when a supplier uses an optimally positioned delivery window to minimise the expected cost of untimely delivery. The scale parameter increases the expected penalty cost, skewness decreases the cost and the location parameter has no effect on the expected penalty cost. The effects are illustrated in a numerical example with real-world supplier data. The results can be used in developing strategies for improving delivery performance from a supplier's perspective and define how the delivery time distribution parameters can be modified to decrease the expected penalty cost of untimely delivery. The paper proposes a general approach to modelling delivery performance improvement and can be applied to other delivery time distribution forms. The approach can serve as guidance for practitioners undertaking a programme to improve delivery performance. [ABSTRACT FROM AUTHOR]

Distribution networks often manage products with varying life cycles, where demand for some products is relatively stable throughout the year (basic) and the demand for others is short-lived (fashion). Beyond the coordination of inventory and transportation decisions, decisions at the warehouse must be considered as its resources are frequently shared by both product classes simultaneously. For this two-product class distribution planning problem, we focus on characterising three real-world distribution strategies observed in industry and evaluating them based on total distribution cost and warehouse measures (e.g. workforce plan and workload variation) against a benchmark ILS-based heuristic. Experimental results suggest that there are in fact strategies in industry that under specific system configurations may provide competitive solutions compared to the benchmark heuristic on large problem instances (e.g. 200 stores, 1000 products, and 28 days). Several managerial insights are derived to compare such distinct warehouse strategies and the corresponding impact on the network. [ABSTRACT FROM AUTHOR]

In this paper, imperfect multi-item production inventory models are considered over a finite time horizon with known dynamic demands. The production rates are functions of time which are taken as control variables. In the production process, reliability plays an important role to improve the quality of products and to decrease the defective rate. The said defective units are partially or fully reworked. The unit production cost is a function of production rate and also dependent on raw material cost, development cost due to reliability and wear-tear cost. There is a constraint on the total production cost termed as budget constraint which is crisp/imprecise/random in nature. The objective of the present investigation is to fix the optimum reliabilities of the production system to have maximum return. Thus, the models are formulated as optimal control problems for the maximisation of profit and solved using Hamiltonian (Pontryagin’s Maximum Principle), fixed-final time and free-final state system, Kuhn–Tucker conditions and Generalised Reduced Gradient Method. Several particular cases are derived from the general model. The models are illustrated numerically and graphically and some managerial decisions are derived. [ABSTRACT FROM PUBLISHER]

In many industries, distribution activities are realised in a dynamic environment including uncertainties. Besides, adding transportation mode alternatives, inventory-stocking opportunities in wholesalers, unmet demand permission in distribution centres, etc. increase the difficulty of problem modelling and solving for large-scale networks. In this study, the problem of physical distribution network (DN) design with profit maximisation objective function is modelled to tackle with realistic cases. Two-stage stochastic mixed-integer programming method is used to handle the uncertainties and to consider the probable scenarios. The first-stage decisions of the proposed model are related with the selection of facility location in strategic level, and the second-stage decisions are related with the transported and stocked products or unmet demand quantities. Here, a multi-product, two-echelon, multi-mode and multi-period network model is applied to a hypothetically created problem, inspired from the physical DN of home appliance companies. Various scenarios including stochastic demand and price data with different realisation probabilities are used in the model. The motivation of this study is the lack of reaching a global optimum result using transportation modes as stochastic parameters, considering their own lead times and capacities. Finally, various results are obtained for different cases and analysed in detail. [ABSTRACT FROM PUBLISHER]

Although it is an essential link in any supply chain, transportation is often neglected in inventory decisions. In reordering decisions, for example, this omission may well result in unexpected losses, as transportation and quantity discounts can be tricky. In this paper, we study the problem of optimal coordination of these discounts from the perspectives of the parties who offer them, rather than of those who take them. Using a non-cooperative model of a three-party supply chain, we show that cooperation can benefit each member individually, and the supply chain overall. In fact, cooperation can generate a non-empty core – that is, there may be a surplus that can be allocated so that all parties and all coalitions of parties, are induced to continue to cooperate. We provide a detailed algorithm, based on the Shapley value, to allocate the surplus fairly and illustrate it with numerical examples. [ABSTRACT FROM AUTHOR]

The standard literature on inventory modelling is rarely differentiating between the inventory records and the physical inventory. In the recent years, some empirical studies highlighted that errors and inventory perturbations may occur in the inventory system. Such errors result in a gap between what the informational system (IS) shows and what is actually available for sales and used to satisfy the demand. The impact of such errors is particularly important in a wholesaling/e-retailing context where customer’ demands are remotely satisfied based on the inventory records shown in theIS. These errors could be modelled by an additive or multiplicative structure depending on the link between the error variability and the ordered quantity. The aim of the paper is to extend the existing literature by developing an inventory framework that permits the analysis and the performance improvement of an inventory system subject to a multiplicative errors setting. The multiplicative and stochastic settings also known as the stochastically proportional modelling of errors is not well developed in the literature despite the fact that such an assumption bears considerable association with reality. We provide comprehensive analytical and numerical studies and we also complete our contribution by a comparison between the additive and the multiplicative error settings where we derive interesting managerial insights about the impact of wrongly modelling errors. We also focus on the benefit of applying our results compared with the case where errors are ignored or not known. [ABSTRACT FROM PUBLISHER]

In a manufacturing system, a just-in-time (JIT) procurement and supply system is important for reducing cost and responding to customer’s requirement quickly. Successful implementation of a JIT system needs supplier/manufacturer cooperation in small lot-size delivery and inbound logistics cost reduction. In this study, an integrated optimal model of inventory lot-sizing vehicle routing of multisupplier single-manufacturer with milk-run JIT delivery is established. A novel method for computing transportation cost is proposed. Because the integrated model is a NP-hard problem, a meta-heuristic algorithm of ant colony optimisation is developed for solving the model. Numerical examples are used to demonstrate and test the effectiveness of the model and the algorithm. The results show that integrated model with milk-run delivery can reduce the total cost and realise the JIT production and procurement philosophy which emphasises small lot-size production and delivery. The results highlight the importance of cooperation between suppliers and manufacturers in JIT production practices. [ABSTRACT FROM PUBLISHER]

The paper investigates newsvendor problem for a dyadic supply chain in which both the supplier and the retailer have the preference of status-seeking with fairness concerns. Nash bargaining solution is introduced as the fairness reference point and equilibrium results are derived. The effects of fairness-concerned status-seeking behaviors on optimal decisions as well as channel efficiency are further analyzed. It is shown that the channel efficiency will decrease because of such behavioral preference. The retailer’s share will be larger when the supplier concerns fairness less, and the supplier’s sensitivity to fairness plays a relatively more important role for the channel efficiency. Additionally, another interesting managerial insight is concluded that fairness concerns will not change the status of channel coordination in certain conditions. More specifically, those contracts able (unable) to coordinate fairness-neutral supply chain, based on affine transformations with scale factors within certain ranges, still succeed (fail) to coordinate the fairness-concerned. Furthermore, several insights on bargaining powers are given as well. [ABSTRACT FROM PUBLISHER]

The inventory-routing problem (IRP) is a typical logistics optimisation problem that supply chains, implementing vendor managed inventory (VMI), are confronted with. It combines inventory control and vehicle routing. The main objective of the IRP is to jointly determine optimal quantities of the product to be delivered to the retailers, delivery periods and optimal vehicle routes for the shipment of these quantities. This paper considers a multiperiod inventory-routing problem with stochastic stationary demand rates (MP-SIRP). The problem is first formulated as a linear mixed-integer stochastic program for which we propose a deterministic equivalent approximation model (MP-DAIRP). This latter model can be decomposed into two well-know subproblems: an inventory allocation subproblem and a vehicle routing subproblem. The stochastic aspect of the demand is accounted for in the inventory allocation subproblem. The vehicle routing subproblem is solved as a deterministic mixed-integer problem. Lagrangian relaxation is used to determine close to optimal feasible solutions for the MP-DAIRP. Results of the proposed Lagrangian relaxation approach on some numerical examples are reported and thoroughly discussed. [ABSTRACT FROM AUTHOR]

Vendor selection in supply chain is a multi-criteria problem that involves a number of quantitative and qualitative factors. This paper deals with a concrete problem of flour purchase by a company that manufactures bakery products. The selection process is driven by the price, reliability and quality objectives of the buyer and is subject to the capacity constraints of the vendors in the situation where all suppliers offer several kinds of flour (multiproduct situation). Vendors often offer quantity discounts, i.e. the purchasing price of flour depends on the quantity ordered. The multiproduct situation complicates the mathematical formulation of the problem and in this context it is much more convenient to consider the discounts of the money volume of business with every vendor. This problem has been solved using an integration of analytic hierarchy process (AHP), weighted sum model (WSM) and fuzzy multi-objective mixed-integer programming to define the optimum quantities among the selected suppliers. [ABSTRACT FROM AUTHOR]

We propose a new optimisation approach to address a multi-period, inventory control problem for an assembly system under stochastic environment. Significant drawback in a construction of a real-life model for a multi-product, multi-component assembly system is the fact that the shortage cost is typically known for a final product while the optimisation is carried out on assembly components. In the cases when the same type of components assemble different types of finished products, this becomes insuperable obstacle for most of the known approaches. In addition, restrictive assumptions about component demand are common for number of published models. Therefore, we develop a framework, which has the ability to incorporate real shortage costs of the final products within the optimisation process and to incorporate more realistic assumptions about product demand. The aim is to define a completely new optimisation approach in the case of complex component’s interdependencies in assembly systems. The inclusion of the proposed model in the optimisation process is shown by the example of a known simple stochastic demand model. Simple SQL procedures have been presented which benefits from the relational structure of the problem. [ABSTRACT FROM PUBLISHER]

A supply chain ecosystem consists of the elements of the supply chain and the entities that influence the goods, information and financial flows through the supply chain. These influences come through government regulations, human, financial and natural resources, logistics infrastructure and management, etc., and thus affect the supply chain performance. Similarly, all the ecosystem elements also contribute to the risk. The aim of this paper is to identify both performances-based and risk-based decision criteria, which are important and critical to the supply chain. A two step approach using fuzzy AHP and fuzzy technique for order of preference by similarity to ideal solution has been proposed for multi-criteria decision-making and illustrated using a numerical example. The first step does the selection without considering risks and then in the next step suppliers are ranked according to their risk profiles. Later, the two ranks are consolidated into one. In subsequent section, the method is also extended for multi-tier supplier selection. In short, we are presenting a method for the design of a resilient supply chain, in this paper. [ABSTRACT FROM PUBLISHER]

We consider a decentralised supply chain with demand uncertainty, wherein a manufacturer sells a single product that consists of two components to the end consumer through an independent distributor. Assume that one component has a random yield, the manufacturer may rely on the spot market to replenish any shortage components after the random yield is realised. We identify the optimal product order, component production and replenishment decisions under two different situations. One is the traditional arrangement that the distributor decides the product procurement quantity and the manufacturer chooses the production quantity. The other is vendor-managed inventory (VMI) arrangement in which the manufacturer is responsible for both the order and the production decisions. The results show that the role of spot market can effectively offset the negative effects from production yield’s, market demand’s and component spot price’s variances. Consequently, the spot market leads to the cooperation between the manufacturer and the distributor, and improves the channel’s overall performance, in particular under the VMI arrangement when the wholesale price is sufficiently high. [ABSTRACT FROM PUBLISHER]

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches. [ABSTRACT FROM PUBLISHER]

Introducción: Las empresas de los canales de distribución tienen como principal función intermediar transacciones entre los proveedores y reventas. Además, ellos sirven como agentes entre los revendedores y los usuarios finales comisionando a la reventa. Este artículo fue desarrollado en una distribuidora nacional de automatización, con 20 años en este mercado y que presenta problemas en el stock como rupturas y excesos, buscando acciones para minimizar estés problemas principales. Objetivo: El objetivo de la investigación fue analizar y contextualizar estas variables, pudiendo así identificar sugerencias de acciones de mejoras de cómo evitar problemas en la gestión de inventarios. Materiales y métodos: La metodología utilizada fue el análisis cualitativo, teniendo como método de investigación el estudio de caso. Se aplicó un cuestionario estructurado y evaluado la información de la base de datos de la empresa. Se elaboró un diagrama de flujo del sector de compras y stock para mapear el funcionamiento del sector. Resultados: Los resultados de la investigación evidenciaron que la empresa cree que tiene un control de inventario adecuado, pero identificó la necesidad de mejoras, debido a las frecuentes rupturas en el stock, así como los excesos de ítems con bajo giro de ventas. Conclusiones: Se han determinado herramientas e indicadores de gestión de stocks para controlar los problemas de distribución logistica. [ABSTRACT FROM AUTHOR]

Stochastic inventory control in multi-echelon systems poses hard problems in optimisation under uncertainty. Stochastic programming can solve small instances optimally, and approximately solve larger instances via scenario reduction techniques, but it cannot handle arbitrary nonlinear constraints or other non-standard features. Simulation optimisation is an alternative approach that has recently been applied to such problems, using policies that require only a few decision variables to be determined. However, to find optimal or near-optimal solutions we must consider exponentially large scenario trees with a corresponding number of decision variables. We propose instead a neuroevolutionary approach: using an artificial neural network to compactly represent the scenario tree, and training the network by a simulation-based evolutionary algorithm. We show experimentally that this method can quickly find high-quality plans using networks of a very simple form. [ABSTRACT FROM AUTHOR]

Consider a supply chain where the retailer faces a stochastic demand and orders from the supplier, while the supplier manufactures new products and also remanufactures early returns to meet the order. The order and manufacturing quantity decisions are studied under three decentralised cases: (1) the Stackelberg case, where the manufacturing quantity is determined by the supplier after realising the order quantity from the retailer; (2) the Nash case, where the manufacturing and order quantities are determined simultaneously; (3) the inaccessible return information case, where the retailer does not have the distribution information of upstream returns. We find that in the Stakelberg case the order and manufacturing quantities are larger than in the inaccessible return information case, and the profits for the supplier and retailer are also higher. In contrast, the quantities and profits in the Nash case are the lowest of the three cases when the returns are negatively correlated to the demand. The centralised system is also explored by solving a two-step dynamic program. Computational results are reported to show the effects of system parameters. [ABSTRACT FROM AUTHOR]

The design for manufacturability (DFM) method is most effective when integrated with the new product development (NPD) process. Due to the focused nature of the associated product and process knowledge and the extensive effort required, there are many NPD situations where classical DFM techniques cannot be readily applied. In this paper, Pro-DFM a multi-criteria model for manufacturability analysis that identifies product realisation opportunities (PRO) for cost reduction is presented. The key assumption in Pro-DFM is that the NPD team has a baseline estimate of production costs, and the evaluation question is how DFM issues will affect the expected unit production cost. The Pro-DFM model analyses a new design in three different factors: part procurement and handling, product assembly fabrication processes, and inventory costs. Each of these is independently analysed using a hierarchy of multiple criteria and sub-criteria. This approach is found to be amenable to most NPD processes, and conducive to easy integration. Each evaluation sub-criterion is presented in the form of a simple query, which is associated with a set of responses that is flexibly anchored to a uni-dimensional scale. A case study example is used to demonstrate the DFM evaluation process and the derivation of the cost penalties. [ABSTRACT FROM AUTHOR]

Inventory control is a critical problem in manufacturing systems. Inventory shortage significantly affects system productivity, while excessive stocks increase the operation cost. It is difficult to avoid fully inventory shortage under mass customisation manufacturing based on product configuration. In this paper, we propose a new approach for inventory-shortage driven optimisation of dynamic product configuration variation to meet the requirements of product configuration change and find suitable combination of parts by considering cost, lead-time and inventory variation. The multi-objective optimisation model uses a multi-objective genetic algorithm and adds impact cost, lead-time and inventory factors to the normal configuration optimisation model. An industrial case study demonstrates the practicality and effectiveness of the proposed approach. By means of this research, valid solutions for configuration variation are available to the decision makers. [ABSTRACT FROM AUTHOR]

A closed-loop supply chain system is investigated. This system consists of a retailer, a manufacturer, a supplier, and a collector. The demand of the retailer is satisfied either by newly manufactured products or by remanufactured products which are comparable to the new ones in function and quality. We apply one manufacturing cycle and at least one remanufacturing cycle policy and at least one manufacturing cycle and one remanufacturing cycle policy to the manufacturer's manufacturing and remanufacturing operations, and give the corresponding procedures to determine the optimal system policy in the completely decentralised decision-making case and the completely centralised decision-making case by elimination theory and the difference function. A numerical comparison of our results with those of Chung et al. (2008. Optimal policy for a closed-loop supply chain inventory system with remanufacturing. Mathematical and Computer Modelling, 48 (5-6), 867-881) is also performed. The results are general since the manufacturer tends to adopt one manufacturing cycle and at least one remanufacturing cycle policy when the return rate is higher; otherwise, the manufacturer tends to adopt at least one manufacturing cycle and one remanufacturing cycle policy. [ABSTRACT FROM AUTHOR]

In this paper, we focus on a production system where a single product is manufactured on a single facility and delivered to the subsequent stage in batch shipments. In contrast to earlier works, we assume that the inventory on the producing stage is depleted at discrete time intervals, and analyse the effect of a variable production rate on the inventory build-up and the total costs of the system. We develop formal models for the case of equal- and unequal-sized batch shipments and propose solution procedures for the models. In a numerical study, we illustrate that deviating from the 'design production rate' of a production system may reduce inventory carrying costs and thus lead to lower total costs. [ABSTRACT FROM AUTHOR]

We study a production planning problem of product assembly with random demand, where the customers choose their preferred suppliers for pairs of inter-dependent components through the approved vendor matrix. The problem is to develop production plans that minimise the expected total shortage and holding costs while observing the matrix restrictions and limited component supplies. We provide a mathematical programming formulation of the problem with a large number of decision variables, whose cost function is the solution of a parametric stochastic transportation problem. We present a gradient-based interior-point approach to solve this problem where the gradient is estimated by the shadow price from the solution of such a transportation problem. A column generation scheme is integrated into the approach to handle the large problem issue. Computational results show that our algorithm significantly improves the computational time when compared with the approach without column generation. In addition, we also discuss some extensions of the basic problem to the multi-period rolling horizon case. [ABSTRACT FROM AUTHOR]

This work examines the bullwhip effect generated and suffered by each level of a four-stage beer game supply chain when different demand scenarios are considered. The paper shows that the actors who generate lower bullwhip are those who suffer more from its effects. Moreover, a new definition of an inventory oscillations measure based on bullwhip definition is introduced. Finally the paper verifies that the new measure of inventory oscillations provides more information on supply chain performance than the bullwhip measure. [ABSTRACT FROM AUTHOR]

Consignment stock (CS) is an innovative approach to supply and stock management, based on a strong and continuous collaboration between vendor and buyer to create a 'win-win' situation, where both partners have equal gains. An analytic formulation of CS policy with obsolescence has been proposed in Persona et al. (2005). This article considers new critical factors (present in several industrial environments) providing a logical extension of the above mentioned study. The proposed methodology addresses, in particular, the design of a new stock policy in an industrial environment with demand variability, stock-out risk and limited warehouses space. The analytical model presented demonstrates that a traditional stock policy, such as the economic order quantity approach is always more expensive than the consignment stock approach. In addition, the benefits of the CS policy to the supply chain are consistently high including when applied to realities with high demand variation and space limitations. [ABSTRACT FROM AUTHOR]

While the poor response implications of supply are often not elaborated on in the literature, postponement has recently been mentioned as a useful tool for managing supply risk and disruptions. To interpret this in a more complete manner, this paper has attempted to explore the role of postponement in supply chain risk management from a complexity perspective. After a review of the relevant literature, it first draws insights emerging from normal accident theory that addresses the system characteristics of catastrophic accidents and applies them to supply chain disruptions. This is followed by the utilisation of normal accident theory to explain the role of postponement in supply chain risk management. Building on this, this paper also investigates the complexity implications of some commonly recommended measures to mitigate supply chain disruptions. In certain circumstances, the introduction of those measures may add to the complexity of a system and thus become inherently infeasible. The paper concludes with a summary and some suggestions for further research. [ABSTRACT FROM AUTHOR]

This study examines the antecedents and consequences of supply chain activities and empirically tests many of the assumptions in the extant buyer-supplier relationship literature. To analyse the validity of the research model and the hypotheses, data was gathered from 271 manufacturing organisations in South Korea through the administration of structured questionnaires. The results suggest that trust, interdependency, and rate of technological change are major factors that influence the level of operational and strategic information sharing and collaboration, and that the higher the degree of strategic information sharing and collaboration is, the greater the level of effectiveness becomes. However, there is no significant relationship between the length of relationship and information sharing and collaboration. Research and practical implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

There are many reasons for the growing interest in reverse logistics. The most prominent reasons are the growing concern for the environment and cost reduction. Next to environment, consumers demand for clean manufacturing and recycling. Hence, customers and retailers expect original equipment manufacturers to set up a proper reverse logistics system and expect the returned products to be processed and recovered in an environmentally responsible way and another reason is cost reduction. A well-managed reverse logistics programme can provide important cost savings in procurement, disposal, inventory carrying and transportation. In this context, looking at the entire supply chain is the best starting point for solutions. Supply chain management aims at the integration of traditional 'forward' supply chain processes, avoiding local optimisation by emphasising integrality. The main objective of this paper is to design an integrated forward logistics multi-echelon distribution inventory supply chain model (FLMEDIM) and closed loop multi-echelon distribution inventory supply chain model (CLMEDIM) for the built-to-order environment using genetic algorithm and particle swarm optimisation. In this paper, the proposed model is validated by considering two case studies: one for a tyre manufacturer and the other for a plastic goods manufacturer both located in the southern part of India. This paper utilises the multi-echelon distribution inventory supply chain model proposed by Haq and Kannan (2006a) for the FLMEDIM. The software used was written in the Java programming language. [ABSTRACT FROM AUTHOR]

This paper addresses the design of production-distribution networks including both supply chain configuration and related operational decisions such as order splitting, transportation allocation and inventory control. The goal is to achieve the best compromise between cost and customer service level. An optimization methodology that combines a multi-objective genetic algorithm (MOGA) and simulation is proposed to optimize not only the structure of the production-distribution network but also its operation strategies and related control parameters. A flexible simulation framework is developed to enable the automatic simulation of the production-distribution network with all possible configurations and all possible control strategies. To illustrate its effectiveness, the proposed method is applied to a real life case study from automotive industry. [ABSTRACT FROM AUTHOR]

This paper addresses the performance evaluation and optimization of a production-distribution system composed of a warehouse supplied by a manufacturing plant with finite capacity. Customer orders arrive randomly with random order size. Transportation time from plant to warehouse is fixed. We propose an analytical approach that uses only the first two moments of random variables to evaluate the inventory cost and demand fill rate. A gradient-based method is then proposed to minimize the average total inventory cost subject to fill rate requirement. Numerical comparisons with simulation show that the analytical approach is very efficient. [ABSTRACT FROM AUTHOR]

In this research, we administered surveys to operations and supply chain managers from different companies to better understand how they approached quality management. The underlying research question was whether the increased emphasis in supply chain management in the workplace had implications for how quality management is practiced and how quality-related values are emphasised. We found that those who identified themselves as supply chain managers utilised and emphasised quality tools and values to a greater extent than those who identified themselves as operations managers. The tools emphasised by supply chain managers included benchmarking, complaint resolution, design for the environment, ERP, supplier development, focus groups, and supply chain management. The primary theoretical implication of this study is that there exists an emerging field that we can term 'supply chain quality'. This study provides a preliminary outline of the domain of this field. [ABSTRACT FROM AUTHOR]

This paper reports a study on a real three-echelon supply chain operating in the beverage sector. The authors, starting from the actual supply chain configuration, propose a detailed study of the inventory systems. The test of a comprehensive set of different operative scenarios, in terms of customers' demand intensity, customers' demand variability and lead times, becomes a powerful tool for inventory systems analysis along the supply chain. The main objective is the comparison of the actual supply chain configuration with optimistic and pessimistic scenarios for studying the behaviour of different inventory control policies and optimizing the inventory system of each supply chain node. Due to the dynamically changing and stochastic behaviour of the supply chain variables as well as the complex interactions among its actors, the authors have been pushed to implement an advanced simulation model supported by a 'well-planned' experimental design. In addition the paper aims to underline the research effort for conceptualizing, modelling, validating and simulating a real stochastic supply chain. [ABSTRACT FROM AUTHOR]

Effective Supply Chain Management (SCM) is a pivotal issue in the dynamically changing business environment. Dynamic SCM requires integrated decision-making amongst autonomous chain partners with effective decision information synchronization amongst them. By exploiting flexibility in supply chain structures, better performance can be achieved. Similarly, by judiciously employing decision flexibility and the associated dynamic control amongst autonomous supply chain nodes, many improvements are possible. The paper presents a study on the role of different flexibility options (i.e. no flexibility, partial flexibility and full flexibility) in a dynamic supply chain model based on some key parameters and performance measures. Supply chain flexibility has significant potential and needs a greater research attention. The paper attempts to advance the knowledge of dynamic control on effective flexibility exploitation in the context of dynamic supply chains. A simulation model of a dynamic supply chain is used for this purpose. The key results are highlighted along with industry implications. Here each supply chain node involves decision-making. Based on the order and sample information available from the immediate buyers or customers, the supplier selection decisions are dynamically made. A seemingly good decision at a stage based on local information often ends up as detrimental not only to the total chain cost, but also to the total costs of the node itself. These observations are important for the designers and managers of the flexible supply chain systems to arrive at appropriate types and a judicious level of flexibility to attain significant improvements in total cost reduction. The modelling of dynamic supply chains with a focus on flexibility can offer enormous potential to the industry. This paper addresses this interesting and challenging domain. [ABSTRACT FROM AUTHOR]

For many firms, using their supply chains as competitive weapons has become a central element of the strategic management process in recent years. Drawing on the resource-based view and theory from the organizational learning and information-processing literatures, this study uses a sample of 201 firms to examine the influence of a culture of competitiveness and knowledge development on supply chain performance in varied market turbulence conditions. We found that synergies exist between a culture of competitiveness and knowledge development: their interaction has a positive association with performance. In addition, based on behavioral and contingency theories, we found that market turbulence moderates these relationships, having a positive influence on the knowledge development–performance link and a negative influence on the culture of competitiveness–performance link. Managers who are confident about the level of market turbulence they will face can use this sense to decide whether to emphasize developing either a culture of competitiveness or knowledge development in their supply chains. For those firms whose managers are unlikely to be able to predict the degree of turbulence they will face over time, a focus on both a culture of competitiveness and knowledge development is critical to ensuring success. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We present an efficient and accurate approximate analytical decomposition method for evaluating the production rate and distribution of inventory of a closed-loop manufacturing system with unreliable machines and finite buffers. It is based on an earlier decomposition for a tandem line; it differs only in accounting for the different sets of machines that could cause blockage or starvation to other machines. The method can be applied to tandem production lines with a limited number of pallets or fixtures; the pallets travel in a closed loop even though the parts do not. It can also be applied to systems controlled by a CONWIP policy with infinite or finite buffers since such a policy can be implemented with a limited number of tokens that behave in the same way as pallets. [ABSTRACT FROM AUTHOR]

Given the size, complexity and dynamic nature of many supply chains, there is a need to understand the impact of disruptions on the operation of the system. This paper presents a network-based modelling methodology to determine how changes or disruptions propagate in supply chains and how those changes or disruptions affect the supply chain system. Understanding the propagation of disruptions and gaining insight into the operational performance of a supply chain system under the duress of an unexpected change can lead to a better understanding of supply chain disruptions and how to lessen their effects. The modelling approach presented, Disruption Analysis Network (DA_NET), models how changes disseminate through a supply chain system and calculates the impact of the attributes by determining the states that are reachable from a given initial marking in a supply chain network. This ability will permit better management of the supply chain and thus will allow an organization to offer quicker response times to the customer, lower costs throughout the chain, and to the end customer higher levels of flexibility and agility, lower inventories throughout the chain (both with work-in-process and inventories), lower levels of obsolescence and a reduced bullwhip effect throughout the chain. This is of particular benefit in large-scale systems, since it can give the user the ability to perform detailed analysis of a dynamic system without the computational burden of a full-scale execution of the model. Consequently, the model may then be segmented to evaluate only the portions or sub-networks that are affected by changes in an initial marking. [ABSTRACT FROM AUTHOR]

In view of the slow rate of postponement applications, this paper attempts to examine postponement strategies from an inter-organizational perspective. The paper first reviews the literature on different postponement strategies (including logistics postponement, production postponement, purchasing postponement, and product-development postponement) mainly within the context of the supply chain or supply network. Then, two research questions are formulated. This is followed by the investigation into the inter-organizational structure and capacity planning in postponement applications. The paper concludes with some suggestions for further research. [ABSTRACT FROM AUTHOR]

A mixed-model assembly line comprises a set of workstations in serial and a conveyor moving at a constant speed, which can assemble variety products in different models during a working shift or a working day. Initial-units that belong to different models are successively fed onto the conveyor at a given cycle time length to get into the assembling operations as semi-products. The conveyor moves semi-products to pass through the workstations gradually to complete the assembling operations for generating finished products. A set of warehouses stores finished products, and each model has a specified warehouse. Customers arrive at the warehouses to demand finished products with stochastic demand forms. A daily scheduling task is the determination of the sequence that specifies the feeding order of the models, which must be set out at the beginning of each day. This paper deals with a new goal, 'sequence-to-customer', with stochastic customer demands. An optimization problem is formulated with the objective of minimizing the system cost that includes the holding cost for finished products and the penalty cost for backordered customers during a decision horizon. A lower bound of the system cost is found, which is useful in verifying the optimality of any solution. A heuristic algorithm is proposed to solve the optimization problem, which can obtain optimal solutions or near-optimal solutions with almost ignorable relative errors to optimal solutions. By using the algorithm, the behaviour of the system cost with respect to the variation in customer demands is also investigated to provide insights into management of a mixed-model assembly line. [ABSTRACT FROM AUTHOR]

This paper presents a computational intelligence approach, which addresses the bullwhip effect in supply chains (SCs). A genetic algorithm (GA) is employed to reduce the bullwhip effect and cost in the MIT beer distribution game. The GA is used to determine the optimal ordering policy for members of the SC. The paper shows that the GA can reduce the bullwhip effect when facing deterministic and random customer demand combined with deterministic and random lead times. The paper then examines the effect of sales promotion on the ordering policies and shows that the bullwhip effect can be reduced, even when sales promotions occur in the SC. [ABSTRACT FROM AUTHOR]

Business-to-business information technology systems are becoming increasingly important in firm supply chains. Utilizing the concept of modularity, this article clarifies the strategic implications of B2B technology. There are two generic B2B strategies: modularization, which allows a firm to rent out its internal capabilities to others in its industry; and architectural entrepreneurship, which alters the supply chain by allowing a central coordinating firm to facilitate arrangements that trust issues and information asymmetries had previously made impossible. Which modular strategy is appropriate depends on the role the focal firm plays in the supply chain and their supply chain indispensability. Only firms with deep architectural knowledge can take full advantage of these modular strategies. [ABSTRACT FROM AUTHOR]

Supply chains need to be synchronized lo increase system efficiency. With increasing globalization, an assembly or a manufacturing firm may receive supplies from all over the world. Synchronizalion of such a system becomes difficult for two reasons: first, each supplier has certain capacity and can supply materials with a fixed but different order processing time; second, each supplier has a different cost structure and, therefore, production quantities differ due to incentives conflicts, which leads to local optimization of profits by the suppliers. In the existing literature, this problem is generally tackled by focusing either on the synchronization of order processing time or on order quantity determination. However, when system coordination is of the essence, simultaneous consideration of both becomes imperative. A model to synchronize the assembly process is proposed and the optimal order quantities in a two-echelon assembly system with one assembler (facing a stochastic demand) and multiple suppliers with deterministic order processing times is determined. A numerical study conducted shows that risk sharing and proper safety stock placement lead to better system coordination and improve system performance. [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of three routing policies in the order-picking process, i.e. return, traversal, and midpoint policy. It is assumed that items are assigned to storage locations on the basis of the cube-per-order index (COI) rule in a low-level picker-to-part warehousing system. First, for the three policies, analytical models are developed for the total expected travel distance of the order picker considering the number of the stocking aisles is even or odd. Then the developed models are compared with simulation results to show the validity. Finally, the performance of the three policies is examined by varying the parameter value of the COI-based ABC curve, number of picks in the pick list, and ratio of the length to the width of the warehouse. [ABSTRACT FROM AUTHOR]

The economic performance of a generalized Order-Up-To policy is investigated in response to an Auto Regressive stochastic demand process. Focus is on the case where the physical production/distribution lead time is one period and where demand is forecasted with simple exponential smoothing. Two sets of convex piece-wise linear costs are considered. The first set is the traditional inventory holding and backlog costs. The second set of costs is piece-wise linear and increasing convex costs associated with the production order rate within and above a capacity constraint. Numerical investigations reveal that the classical Order-Up-To policy is no longer optimal when a broader range of costs is considered in the objective function. [ABSTRACT FROM AUTHOR]

This research investigates the impact of different levels of sharing information on inventory replenishment of enterprises in three-stage distribution supply chains of the divergent type. This paper has two objectives: (1) to investigate the effects of different levels of information sharing on operating cost, inventory level and backlog level of retailers, distributors, manufacturer and the entire supply chain; and (2) to study which level of information sharing is most beneficial or optimal to each type of enterprise. The entire supply chain under various supply chain scenarios characterized by several parameters including demand variance, lead times, capacity and order batch size is investigated. The impact of sharing information is evaluated in terms of several performance indicators through a multi-agent-based simulation model. The results of the experimental simulation show that no single level of information sharing dominates the others from the perspective of individual enterprises. Some insights are provided for managers who want to implement information sharing. [ABSTRACT FROM AUTHOR]

The article describes the processes involved in designing a packaging take-back system adopted by Quantum Corporation. Because of rapidly changing technology and production methods, product-specific environmental improvements are difficult to facilitate. This had lead firms to examine their packaging, purchasing, facilities management, and supplier networks in search of new ways to reduce the environmental burden of their products. The author notes the opportunities for improvement in packaging waste and the effects of transportation of electronics. The article looks at the Quantum Corporation, a computer storage products company, which designed a new packaging system for their hard disk drives. All major customers of the company gave permission to receive reusable packaging.

Managing a distribution system requires the right inventory in the right place at the right time. A Theory of Constraints replenishment solution is presented to aggregate inventory buffers at the central warehouse in plant and change the mode of operation from push to pull. The solution is powerful, .but the optimal amount of buffer remains undetermined. In Theory of Constraints, choosing a specific buffer size is not crucial if the buffer is accurately monitored in a timely manner. Accordingly, Theory of Constraints is offered a buffer management approach for monitoring the buffer. Such buffer management is feasible and effective but is insufficiently rigorous. This paper elucidates a generic buffer management procedure, based on the concept of Theory of Constraints buffer management that rigorously defines a method of monitoring to size and adjust the buffer. An example demonstrates the feasibility of the proposed generic buffer management procedure. [ABSTRACT FROM AUTHOR]