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Transportation problems experienced by UD. Raja Wangi in distributing Maha Dewa fragrant incense. UD. Raja Wangi incurs high transportation costs due to irregular direct distribution patterns and has not paid attention to the route to be passed. One way to solve the problem is to use transportation methods to get the optimal distribution route so that the transportation costs incurred are minimal. This study aims to solve transportation problems using the Bilqis Chastine Erma (BCE) method and the Sumathi Sathiya method with the Stepping Stone method to obtain the optimal solution. The Bilqis Chastine Erma (BCE) and the Sumathi Sathiya methods are indirect methods of solving transportation problems by obtaining an initial solution. After obtaining the initial solution, the Stepping Stone method is used to obtain the optimal solution. The results showed that the optimal solution using the Stepping Stone method based on the initial solution of the Bilqis Chastine Erma (BCE) method obtained a total transportation cost of Rp42,937.00 while the optimal solution using the Stepping Stone method based on the initial solution of the Sumathi Sathiya method obtained a total transportation cost of Rp38,727.00. In addition, the Sumathi Sathiya method gets a difference in total transportation costs of Rp11,790.00 or 23% of the total transportation costs incurred by the UD. Raja Wangi. Therefore, the Sumathi Sathiya method is the best solution for minimizing transportation costs.

The following article examines the cascading effects that took place from February 11–20, 2021, through the perspectives of emergency managers, FEMA employees, and others who responded to "The Texas Freeze." The research discusses the literature on cascading disasters as well as the methodology that was utilized to conduct this study. It then examines the unique challenges experienced before and after the storm. In particular, the article explores the loss of power that subsequently resulted in the lack of water, the freezing of pipes, and flooding. In addition, it mentions other problems such as transportation and the provision of fuel as well as numerous consequences that posed considerable challenges for hospitals, long-term care facilities, and emergency managers. The article concludes with recommendations to strengthen infrastructure, mitigate winter storms, and increase planning and preparedness for complex disasters. The main point to be made is that far more consideration needs to be given to proactively understand and anticipate cascading disasters. [ABSTRACT FROM AUTHOR]

Urban settlements often deal with the massive transportation problems caused by mixed land-use development and improper travel services. This situation propels travel accessibility issues within urban centers. This research is intended to focus on the 3rd largest city of Pakistan's Sindh province, i.e., Sukkur, where residents were found struggling to reach their desired destinations. The study area has naturally grown without planning guidelines, generating traffic congestion and haphazard land-use patterns. This research aims to measure accessibility within the city center using trip rate analysis and a GIS-based isochrone model (1-km radius). In total, 234 household trips were randomly considered according to Morgan's sampling standards. The results revealed that scattered locations caused heavy traffic volumes without public transport facilities. The ratio of traveling by bike for shopping was recorded at 17.24%. Commuting by car; home-based, health, and shopping trips were ranked 1st (5.52%), 2nd (2.76%), and 3rd (1.38%), respectively. The isochrone-based maps were delineated to clarify the temporal accessibility features. Only three shopping activities were found to be accessible within 6 min. Most of the banks were found to be highly accessible. None of the health facilities were located within a 0–6 minute isochronal boundary. Two entertainment sites were accessible within 0–6 min. The residential neighborhoods were not close to the city center. Only three parks and six religious facilities were accessible within 6–12 min. The study findings clarified mixed land use activities accessed through multiple travel modes in the city center. Executing traffic management implications is a need of the time to induce sustainable transportation guidelines. Besides, the results may contribute to SDG 11.2, i.e., "affordable and sustainable transport systems" available for local commuters. The findings of this study are also relevant to evaluating the progress of some cities on SDG 11.2 regarding accessing feasible transportation services. [ABSTRACT FROM AUTHOR]

The problem of limited interest in public transportation due to the restricted coverage of bus rapid transit (BRT) services can be addressed by enhancing door-to-door options. Providing feeder services to assist users in their journeys from start to finish is crucial to achieving this. One suggested feeder option is bicycles because they are faster than walking and eco-friendly. However, in Yogyakarta, there is currently no integration of bike lanes with BRT lanes, making it difficult to promote multimodal transportation. In addition to planning routes, it is important to consider the characteristics of BRT users when implementing multimodal transportation. This helps determine the BRT user category, enabling customized and prioritized service delivery. This study explores the factors that encourage users to use bicycles as feeders and offers insights into users' preferences for cycling facilities. Data were collected through a questionnaire distributed to 200 BRT users selected randomly over 30 days. Based on the model tested using multiple regression analysis, the most popular and confident travel destination for BRT users is their workplace. Moreover, BRT users prefer bicycle lanes that are separate and distinct from other vehicle lanes and convenient bicycle parking locations near bus stops. This research provides valuable recommendations for all stakeholders, particularly the government, to enhance and sustainably improve public transportation services. [ABSTRACT FROM AUTHOR]

Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some modifications to the classical transport task have also been developed. Methods: The article uses the methods of linear optimization. Based on these methods, two modified transport task models have been constructed, which consider the possibility of planning in advance the quantities available from the suppliers of the transported cargo. These models are applicable in SCM for pharmaceuticals with a national logistics hub. Furthermore, a solver in MS Excel is used to determine the optimal solution of optimization models. Results: Two new (modified, extended) models of the transport task have been constructed, in which a preliminary planning of the available quantities of the transported cargo at the suppliers is made. These quantities shall be planned in such a way as to ensure a minimum total transport cost. Conclusions: By applying the proposed new transport task models, lower total transport costs for carrying out imported pharmaceuticals can be ensured compared to an application of the classical transport task model. [ABSTRACT FROM AUTHOR]

The daily functioning of civilization depends heavily on transportation. In most cities, a sizable section of the working class consistently attends both employment and education. There are many different things you can do when commuting, such as unwinding, eating out, and other things. The most popular means of transportation in North Cyprus, particularly in developing cities, is island transportation, which includes the usage of both private cars and commercial vehicles. The advent of edge computing, which offers the opportunity to connect potent processing servers next to the mobile device, is a significant step toward improving user experience and reducing resource use. Mobile Edge Computing is the next trustworthy approach for how mobile devices consume communications and computing. Offloading computation is a key component developing mobile edge computing, which enables devices to get around clustering techniques' limitations and get around computing, storage, and energy constraints. However, computation offloading is not always the best strategy to use; making choosing unloading is a critical step that requires consideration of numerous factors. For instance, shifting the high-resource node to an edge server and granting similar capabilities to the low-resource nodes would delegate heavy duties to the external unit inside the network. The evaluations' results were noteworthy and substantial. Problems involving the vehicles of institutions and organizations can be resolved using the suggested solution to the school bus routing issue. We also test the impact of network latency on the delivery of a particular result using an Edge Computing simulator. [ABSTRACT FROM AUTHOR]

Transportation is extremely important in society's day-to-day operations. A major portion of the working class in most cities go to work and school regularly. Commuting can be used for a variety of reasons, including relaxation, dining out, and other activities. Land transportation, which includes the use of both individual and commercial cars, is the most frequent mode of transportation in North Cyprus, particularly in emerging cities... Commercial transportation, on the other hand, has a significant cost benefit over having a personal vehicle. Taxis are becoming increasingly popular, particularly in the cities of Nicosia, Famagusta, and Karenina. Before, the institutions providing such services were unable to reach as many people as they would have liked, particularly in rural areas. Given the widespread use of smartphones in this area, there is an urgency to reach more customers while taking care of the existing ones. Some businesses in North Cyprus have implemented mobile applications to be used by their consumers, but North Cab Taxi is still a work in progress. Instead, the company uses a Web-based cab reservation system. North Cab has realized the necessity for a smartphone version of its cab booking service for it to keep a competitive step above its competition. [ABSTRACT FROM AUTHOR]

Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some modifications to the classical transport task have also been developed. Methods: The article uses the methods of linear optimization. Based on these methods, two modified transport task models have been constructed, which consider the possibility of planning in advance the quantities available from the suppliers of the transported cargo. These models are applicable in SCM for pharmaceuticals with a national logistics hub. Furthermore, a solver in MS Excel is used to determine the optimal solution of optimization models. Results: Two new (modified, extended) models of the transport task have been constructed, in which a preliminary planning of the available quantities of the transported cargo at the suppliers is made. These quantities shall be planned in such a way as to ensure a minimum total transport cost. Conclusions: By applying the proposed new transport task models, lower total transport costs for carrying out imported pharmaceuticals can be ensured compared to an application of the classical transport task model.

The paper undertakes a critical assessment of the use of smartphone apps for transportation by people with intellectual disabilities. Although apps for transportation such as Uber and Careem have been developed to assist people with disabilities and have numerous benefits, people with intellectual disabilities tend to encounter their own set of difficulties in accessing these apps. This paper presents the research findings drawn from a focus group discussion conducted with nine people with moderate to mild intellectual disabilities in Riyadh, by using a qualitative study focussed on the interpretative paradigm. From the interview findings, some relevant themes were identified. These were: transportation issues encountered by people with intellectual disabilities, the extent and manner of the use of smartphone apps for transportation, the benefits enjoyed by those individuals in using smartphone apps for transportation and the difficulties encountered by them. The paper also discusses the implications for practice and presents some useful recommendations, including the need for family support and government assistance. Smartphone apps introduced specifically for transportation can be extensively supportive for individuals with intellectual disabilities prominently in terms of ease of use, low cost and flexible navigation. It is found that smartphone apps for transportation have been contributory in fulfilling the mobility requirements of intellectually disabled people. Transportation apps like Careem and Uber are very much popular in Saudi Arabia, specifically among people with intellectual disabilities. Such people frequently use the apps and are happy with their key attributes in addressing their transportation issues. The apps can be further promoted by responsible authorities for facilitating people having intellectual disabilities with strengthened and easy access to learning and working opportunities. Further research studies can be organized with a focus on determining creative ways in which technology integration can play a role in improving the mobility and fostering social inclusion of persons with intellectual disabilities. Government authorities can impose policies and measures for safeguarding the rights of this particular group and advancing awareness among society members for collectively working towards their well-being. [ABSTRACT FROM AUTHOR]

The data tend to be centered around a certain value that can be called a central value. In this case, the measures of central tendency are the function used to recognize this central value to represent the data. In some cases, the data are closing to the central value and sometimes more widespread. In order to measure the proximity or distance of data from that central value, measures of dispersion are used. In this research, some of these measures are used to find the basic acceptable solution for transportation problems. Better results are obtained by the researcher through using these measures by taking five applications with different capacities.

In the last decades, research on emergency traffic management has received high attention from the operations research community and many pioneer researchers have established it as one of the most fertile research areas. We consider the computationally hard flows over time problems from wider perspective including flow/time dependent attributes (dynamic flows), a possibility of flows loss on paths while travelling (lossy network problems), arcs/path reversal capability (contraflow models) and possibilities of eliminating merging and crossing conflicts at intersections (abstract flows). The topics also include the networks for relief distribution, location-allocation of facilities, multicriterion characteristics and transit based flow models in brief. The issues are highly motivated from the perspective of traffic control and emergency route choice and scheduling. Despite of many directions such as differential equations for fluid flows, measure and function theory, cell transmission approach and optimal control theory, we have restricted to the perhaps most computationally acceptable research domain, the network flow optimization approach with macroscopic behavior. We compactly review the contributions, explore the featured results, present structured systematic analysis and state the weakness and strength of the models and solution strategies the authors carried out during several years. A large number of problems belong to the category of strongly N P-hard problems and demand efficient computational techniques that at least yield acceptable approximate solutions. This comprehensive survey on evacuation problems complements the number of previous reviews by adding many recent results obtained in the field so far. Moreover, it highlights the main stream research and most promising challenges in modeling and solving more realistic real-life scenarios and explores some possible future research fields.

The current paper focuses on a multiobjective transportation problem which is a special type of vector minimum problem. In order to deal with such a problem, a new model based on fuzzy goal programming is suggested. Different solutions are obtained according to the priorities of the decision maker in the proposed model. With respect to its properties, at least a weakly efficient solution is yielded by solving the new model. To demonstrate the validity and strengths of the suggested model, some numerical examples are given. Further, a comparison is made with different existing methods. [ABSTRACT FROM AUTHOR]

Recently, a new type of transportation problems (named as dual-hesitant fuzzy transportation problem) as well as an approach to find the optimal solution of dual-hesitant fuzzy transportation problems have been proposed in the literature. In this paper, some dual-hesitant fuzzy transportation problems are considered to show that the existing approach is inappropriate as (i) The existing approach fails to find the optimal solution of dual-hesitant fuzzy transportation problems. (ii) On applying the existing approach different optimal transportation costs are obtained corresponding to alternative optimal solutions. Also, to resolve the inappropriateness of the existing approach, a new expression (named as Mehar score function) is proposed to transform a dual-hesitant fuzzy set into a real number. Furthermore, a new approach (named as Mehar approach), based upon the proposed Mehar score function, is proposed to find the optimal solution of dual-hesitant fuzzy transportation problems. [ABSTRACT FROM AUTHOR]

Fractional programming problems take into account the situations where the decision maker is interested to maximize or minimize the ratios of some functions rather than a simple function. Fractional programming modeling approach has a lot of scope in dealing with the transportation planning decision problems. This paper presents a model for transportation problem with multiple fractional objectives involving uncertain parameters. In order to make the model more realistic, we have considered the case when there exists more than one fractional objective. All the parameters involved in the proposed model viz. objective function coefficients, availabilities and demands are assumed to be uncertain. Moreover, an equivalent deterministic model is also presented. Fuzzy goal programming approach is discussed as the solution approach for reaching the compromise solution. A numerical example is also given to illustrate the model more clearly.

The article analyzes and describes theoretical basics of various methods used for lay-out, allocation or solving various types of transportation problems. Lay-out and allocation represent two of the very important decisions which is made by macrologistics management. Nowadays we know several types of solving these problems so it is very important to be able to chose the right way and solve these problems as optimally as it is possible. This article is going to describe some of them.

This study aims to compare demographic and clinical characteristics of chronic obstructive pulmonary disease (COPD) patients who complete and fail to complete outpatient pulmonary rehabilitation (PR) program and to determine the reasons for not completing the program. Patients with COPD referred to the PR program were divided into two groups: Those who completed the program were classified as group 1 and those who did not complete were classified as group 2, and their data were compared. Patients who failed to complete the program were contacted through phone and asked why they ceased their participation in the program. In group 2, number of smoker patients and patients using nebulizer and receiving long-term oxygen treatment, emergency admissions, and dyspnea perception were higher (p = 0.003, p < 0.001, p = 0.033, p = 0.011, p < 0.001, respectively); forced expiratory volume in one second (%) value, exercise capacity, and quality of life were lower (p = 0.024, p = 0.001, p = 0.014, respectively). When considered from the sociodemographic perspective, group 2 had a lower education level and a higher rate of living alone (p < 0.001). Factors impairing the program compliance were lack of motivation (49.0%), transportation problems (23.8%), COPD exacerbation (18.4%), work-related reasons (4.8%), and hospitalization (4.1%), respectively. Smokers and severe COPD patients fail to complete PR program due to various reasons, especially lack of motivation. It is very important for health practitioners to inform patients accurately and adopt a positive attitude. [ABSTRACT FROM AUTHOR]

We consider repeated zero-sum games with incomplete information on the side of Player 2 with the total payoff given by the non-normalized sum of stage gains. In the classical examples the value VN of such an N-stage game is of the order of N or N as N→∞. Our aim is to find what is causing another type of asymptotic behavior of the value VN observed for the discrete version of the financial market model introduced by De Meyer and Saley. For this game Domansky and independently De Meyer with Marino found that VN remains bounded as N→∞ and converges to the limit value. This game is almost-fair, i.e., if Player 1 forgets his private information the value becomes zero. We describe a class of almost-fair games having bounded values in terms of an easy-checkable property of the auxiliary non-revealing game. We call this property the piecewise property, and it says that there exists an optimal strategy of Player 2 that is piecewise constant as a function of a prior distribution p. Discrete market models have the piecewise property. We show that for non-piecewise almost-fair games with an additional non-degeneracy condition the value VN is of the order of N. [ABSTRACT FROM AUTHOR]

Currently, Japan is confronting several major socioeconomic changes, which in turn are the primary causes behind transportation issues surfacing in Japan. These changes in socioeconomics can be identified in the four categories of declining birthrate in an aging population, globalization, technological innovation, and improvements in standard of living. In private and public transportation, technological innovation may impact maintenance of the transportation infrastructure by complicating user behavior. Further, improvements in the standard of living foster expectations of profit from demand for tourism even though these expectations are fraught with issues created by globalization. In terms of traffic safety, strategic measures against accidents are expected, with flags raised regarding changes in human behavior due to technological innovation, and suggestions to aim measures toward bicycle transportation through improved standards of living. By sufficiently investigating these socioeconomic factors that color Japan today and the transportation issues that they cause, other countries that may witness similar experiences may learn important lessons.

Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), etc., for solving emergency transportation problems. We then propose a new hybrid biogeography-based optimization (BBO) algorithm, which outperforms some state-of-the-art heuristics on a typical transportation planning problem.

In the present paper the step fixed charge transportation problem under uncertainty, particularly when variable and fixed cost are given in fuzzy forms, is formulated. In order to solve the problem, two metaheuristic, simulated annealing algorithm (SA) and variable neighborhood search (VNS), are developed for this NP-hard problem. Due to the significant role of parameters and operators on the algorithm’s quality, an extensive calibration in both SA and VNS is carried out with the aid of a set of experimental design. Through extensive computational experiments, appropriate parameter values of the proposed algorithms were chosen. For this purpose, twenty eight problems with different configuration have been generated at random and then the effectiveness of the proposed algorithms was evaluated using the relative percentage deviation (RPD) method.

In this paper, we show that the transshipment problem with a permutable transit vector remains NP-hard even when each entry of the given transit vector takes either zero or two. We prove the hardness by a reduction from an NP-complete problem by the name of 3DM. We also show that the transshipment problem can be solved in polynomial time if each entry of the transit vector takes either zero or one. We obtain the time complexity by applying the successive shortest path algorithm for the minimum cost flow problem.

Finding an exact optimal solution of the Nonlinear Discrete Transportation Problem (NDTP) represents a challenging task in transportation science. Development of an adequate model formulation and selection of an appropriate optimization method are thus significant for attaining valuable solution of the NDTP. When nonlinearities appear within the criterion of optimization, the NDTP can be formulated directly as a Mixed-Integer Nonlinear Programming (MINLP) task or it can be linearized and converted into a Mixed-Integer Linear Programming (MILP) problem. This paper presents a comparison between MILP and MINLP approaches to exact optimal solution of the NDTP. The comparison is based on obtained results of experiments executed on a set of reference test problems. The paper discusses advantages and limitations of both optimization approaches. First published online: 10 Jul 2014

The Nonlinear Discrete Transportation Problem (NDTP) belongs to the class of the optimization problems that are generally difficult to solve. The selection of a suitable optimization method by which a specific NDTP can be appropriately solved is frequently a critical issue in obtaining valuable results. The aim of this paper is to present the suitability of five different Mixed-Integer Nonlinear Programming (MINLP) methods, specifically for the exact optimum solution of the NDTP. The evaluated MINLP methods include the extended cutting plane method, the branch and reduce method, the augmented penalty/outer-approximation/equality-relaxation method, the branch and cut method, and the simple branch and bound method. The MINLP methods were tested on a set of NDTPs from the literature. The gained solutions were compared and a correlative evaluation of the considered MINLP methods is shown to demonstrate their suitability for solving the NDTPs. First published online: 16 Oct 2013

The study examined Florida assisted living facility staff perspectives of disaster preparedness, response, and recovery after the 2004 and 2005 hurricanes. A descriptive study using qualitative and quantitative approaches. One hundred seventy Florida assisted living facility staff who worked in areas under hurricane threat and provided care to residents during a hurricane. A questionnaire that was mailed or administered to staff attending a regional planning conference with quantitative and qualitative items. Of the 143 facilities that were affected by a hurricane, 77 % reported that they sheltered residents in place, while 23 % indicated that they evacuated for one or more of the hurricanes. Almost one-third of facilities lost telephone service and almost half lost electrical power during one or more of the hurricanes. Key topics noted by both evacuating facilities and those that sheltered in place were 1) decision-making, 2) planning, support, and supplies, 3) communication, and 4) electricity. Unique to assisted living facilities is the role of residents' family in assuming responsibility for evacuation and shelter during hurricanes. Facility staff at both evacuating and sheltering facilities indicated that the decision to evacuate or to shelter in place was difficult and the electrical power was critical to resident well-being. Assisted living facilities should develop disaster preparedness plans in conjunction with local and state emergency offices. Adequate disaster preparedness has implications for residents' safety as well as assisted living facility staff during disasters. [ABSTRACT FROM AUTHOR]

Finding an exact optimal solution of the Nonlinear Discrete Transportation Problem (NDTP) represents a challenging task in transportation science. Development of an adequate model formulation and selection of an appropriate optimization method are thus significant for attaining valuable solution of the NDTP. When nonlinearities appear within the criterion of optimization, the NDTP can be formulated directly as a Mixed-Integer Nonlinear Programming (MINLP) task or it can be linearized and converted into a Mixed-Integer Linear Programming (MILP) problem. This paper presents a comparison between MILP and MINLP approaches to exact optimal solution of the NDTP. The comparison is based on obtained results of experiments executed on a set of reference test problems. The paper discusses advantages and limitations of both optimization approaches. [ABSTRACT FROM AUTHOR]

The paper presents possibilities of application of genetic algorithms in design of public transport network. Transportation tasks such as determination of optimal routes and timetable for means of transport belong to difficult complex optimization problems, therefore they cannot be solved using traditional search algorithms. It turns out that genetic algorithms can be very useful to solve these transportation problem. [ABSTRACT FROM AUTHOR]

The Nonlinear Discrete Transportation Problem (NDTP) belongs to the class of the optimization problems that are generally difficult to solve. The selection of a suitable optimization method by which a specific NDTP can be appropriately solved is frequently a critical issue in obtaining valuable results. The aim of this paper is to present the suitability of five different Mixed-Integer Nonlinear Programming (MINLP) methods, specifically for the exact optimum solution of the NDTP. The evaluated MINLP methods include the extended cutting plane method, the branch and reduce method, the augmented penalty/outer-approximation/equality-relaxation method, the branch and cut method, and the simple branch and bound method. The MINLP methods were tested on a set of NDTPs from the literature. The gained solutions were compared and a correlative evaluation of the considered MINLP methods is shown to demonstrate their suitability for solving the NDTPs. [ABSTRACT FROM PUBLISHER]

In this study, the transportation and storage problems for regional power coal allocation planning are formulated as transportation and storage problems to realize the minimization of the regional transportation and storage cost. An effective optimization model is proposed to solve transportation and storage problems for regional power coal allocation planning, which has interactive effect on multiple participants, such as regional power plants, coal transportation companies, logistics centers, and coal storage centers. A case study illustrates that the model and algorithm are more reasonable compared with the classic transportation model, and the sensitivity analysis improves transportation and storage strategies for regional power coal allocation planning. Results demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision-makers (DMs) for reference in favor of exalting decision-making quality. [ABSTRACT FROM AUTHOR]

In this paper we define and study a family of optimization problems called Ferry problems, which may be viewed as generalizations of the classical wolf-goat-cabbage puzzle. We present the Ferry Cover problem (FC), where the objective is to determine the minimum required boat size to safely transport n items represented by a graph G and demonstrate a close connection with Vertex Cover which leads to hardness and approximation results. We also completely solve the problem on trees. Then we focus on a variation of the same problem with the added constraint that only 1 round-trip is allowed (FC1). We present a reduction from MAX-NAE-{3}-SAT which shows that this problem is NP-hard and APX-hard. We also provide an approximation algorithm for bipartite graphs with a factor asymptotically equal to $\frac{4}{3}$ and a 1.56-approximation algorithm for planar graphs. Finally, we generalize the above problem to define FC m, where at most m round-trips are allowed, and MFT k, which is the problem of minimizing the number of round-trips when the boat capacity is k. We present some preliminary lemmata for both, which provide bounds on the value of the optimal solution, and relate them to FC. [ABSTRACT FROM AUTHOR]

We show that any rational convex polytope is polynomial-time representable as a 3-way line-sum transportation polytope of "slim" (r, c, 3) format. This universality theorem has important consequences for linear and integer programming and for confidential statistical data disclosure. We provide a polynomial-time embedding of arbitrary linear programs and integer programs in such slim transportation programs and in bitransportation programs. Our construction resolves several standing problems on 3-way transportation polytopes. For example, it demonstrates that, unlike the case of 2-way contingency tables, the range of values an entry can attain in any slim 3-way contingency table with specified 2-margins can contain arbitrary gaps. Our smallest such example has format (6, 4, 3). Our construction provides a powerful automatic tool for studying concrete questions about transportation polytopes and contingency tables. For example, it automatically provides new proofs for some classical results, including a well-known "real-feasible but integer-infeasible" (6, 4, 3)-transportation polytope of M. Vlach, and bitransportation programs where any feasible bitransportation must have an arbitrarily large prescribed denominator. [ABSTRACT FROM AUTHOR]

We examine a network upgrade problem for cost flows. A budget can be distributed among the arcs of the network. An investment on each single arc can be used either to decrease the arc flow cost, or to increase the arc capacity, or both. The goal is to maximize the flow through the network while not exceeding bounds on the budget and on the total flow cost.The problems are NP-hard even on series-parallel graphs. We provide an approximation algorithm on series-parallel graphs which, for arbitrary δ,#x03B5;>0, produces a solution which exceeds the bounds on the budget and the flow cost by factors of at most 1+δ and 1+#x03B5;, respectively, while the amount of flow is at least that of an optimum solution. The running time of the algorithm is polynomial in the input size and 1/(δ#x03B5;). In addition we give an approximation algorithm on general graphs applicable to problem instances with small arc capacities. [Copyright &y& Elsevier]

This paper discusses analytic algorithms and software for the enumeration of all integer flows inside a network. Concrete applications abound in graph theory, representation theory, and statistics. Our methods are based on the study of rational functions with poles on arrangements of hyperplanes; they surpass traditional exhaustive enumeration and can even yield formulas when the input data contains some parameters. We also discuss the calculation of chambers in detail because it is a necessary subroutine. [ABSTRACT FROM AUTHOR]

The efficiency of AI planning systems is usually evaluated empirically. For the validity of conclusions drawn from such empirical data, the problem set used for evaluation is of critical importance. In planning, this problem set usually, or at least often, consists of tasks from the various planning domains used in the first two international planning competitions, hosted at the 1998 and 2000 AIPS conferences. It is thus surprising that comparatively little is known about the properties of these benchmark domains, with the exception of Blocksworld, which has been studied extensively by several research groups.In this contribution, we try to remedy this fact by providing a map of the computational complexity of non-optimal and optimal planning for the set of domains used in the competitions. We identify a common transportation theme shared by the majority of the benchmarks and use this observation to define and analyze a general transportation problem that generalizes planning in several classical domains such as Logistics, Mystery and Gripper. We then apply the results of that analysis to the actual transportation domains from the competitions. We next examine the remaining benchmarks, which do not exhibit a strong transportation feature, namely Schedule and FreeCell.Relating the results of our analysis to empirical work on the behavior of the recently very successful FF planning system, we observe that our theoretical results coincide well with data obtained from empirical investigations. [Copyright &y& Elsevier]

We consider approximate counting of colorings of an n-vertex graph using rapidly mixing Markov chains. It has been shown by Jerrum and by Salas and Sokal that a simple random walk on graph colorings would mix rapidly, provided the number of colors k exceeded the maximum degree Δ of the graph by a factor of at least 2. We prove that this is not a necessary condition for rapid mixing by considering the simplest case of 5-coloring graphs of maximum degree 3. Our proof involves a computer-assisted proof technique to establish rapid mixing of a new "heat bath" Markov chain on colorings using the method of path coupling. We outline an extension to 7-colorings of triangle-free 4-regular graphs. Since rapid mixing implies approximate counting in polynomial time, we show in contrast that exact counting is unlikely to be possible (in polynomial time). We give a general proof that the problem of exactly counting the number of proper k-colorings of graphs with maximum degree Δ is #P-complete whenever k ≥ 3 and Δ ≥ 3. [ABSTRACT FROM AUTHOR]

A method is given to disaggregate the solution to an aggregated transportation problem. The resulting solution to the original problem is feasible, all-integer, and has lower cost that those of solutions produced by earlier methods. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present a new primal extreme point algorithm for solving assignment problems which both circumvents and exploits degeneracy. The algorithm is based on the observation that the degeneracy difficulties of the simplex method result from the unnecessary inspection of alternative basis representations of the extreme points. This paper characterizes a subset Q of all bases that are capable of leading to an optimal solution to the problem if one exists. Using this characterization, an extreme point algorithm is developed which considers only those bases in Q. Computational results disclose that the new algorithm is substantially more efficient than previously developed primal and primal-dual extreme point ('simplex') methods for assignment problems. [ABSTRACT FROM AUTHOR]

We discuss a wide range of results for minimum concave-cost network flow problems, including related applications, complexity issues, and solution techniques. Applications from production and inventory planning, and transportation and communication network design are discussed. New complexity results are proved which show that this problem is NP-hard for cases with cost functions other than fixed charge. An overview of solution techniques for this problem is presented, with some new results given regarding the implementation of a particular branch-and-bound approach. [ABSTRACT FROM AUTHOR]

A new heuristic procedure for the transportation problem with exclusionary side constraints is developed and implemented. Tabu search, a meta-heuristic method, is used to guide the search to follow a path selectively to prevent from being trapped at local optimal solutions in order to find a global optimal or near global optimal solution. The simplex method on a graph is employed to lead the search from one solution to an adjacent solution in order to take advantage of the underlying network structure of the problem. In the procedure, net changes in cost and in infeasibility are used to measure the attractiveness of a move, and strategic oscillation is used to implement the intensification and diversification functions. A computational experiment was conducted to test the performance of the heuristic procedure and substantial computational results are reported. These results show that the new heuristic procedure finds very good quality solutions and outperforms an existing heuristic procedure in terms of both solution quality and CPU time. [ABSTRACT FROM AUTHOR]

Computing the Kantorovich distance for images is equivalent to solving a very large transportation problem. The cost-function of this transportation problem depends on which distance-function one uses to measure distances between pixels. In this paper we present an algorithm, with a computational complexity of roughly order $$\mathcal{O}$$ (N2), where N is equal to the number of pixels in the two images, in case the underlying distance-function is the L1-metric, an approximation of the L2-metric or the square of the L2-metric; a standard algorithm would have a computational complexity of order $$\mathcal{O}$$ (N3). The algorithm is based on the classical primal-dual algorithm. The algorithm also gives rise to a transportation plan from one image to the other and we also show how this transportation plan can be used for interpolation and possibly also for compression and discrimination. [ABSTRACT FROM AUTHOR]

In the last 20 years many multi-objective linear programming (MOLP) methods with continuous variables have been developed. However, in many real-world applications discrete variables must be introduced. It is well known that MOLP problems with discrete variables can have special difficulties and so cannot be solved by simply combining discrete programming methods and multi-objective programming methods. The present paper is intended to review the existing literature on multi-objective combinatorial optimization (MOCO) problems. Various classical combinatorial problems are examined in a multi-criteria framework. Some conclusions are drawn and directions for future research are suggested. [ABSTRACT FROM AUTHOR]