The transportation problem with stochastic demands PDF Download

Author: David Paul Bernd
Publisher:
ISBN:
Category : Shipment of goods
Languages : en
Pages : 486

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Author: Paolo Toth
Publisher: SIAM
ISBN: 1611973597
Category : Mathematics
Languages : en
Pages : 467

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Book Description
Vehicle routing problems, among the most studied in combinatorial optimization, arise in many practical contexts (freight distribution and collection, transportation, garbage collection, newspaper delivery, etc.). Operations researchers have made significant developments in the algorithms for their solution, and Vehicle Routing: Problems, Methods, and Applications, Second Edition reflects these advances. The text of the new edition is either completely new or significantly revised and provides extensive and complete state-of-the-art coverage of vehicle routing by those who have done most of the innovative research in the area; it emphasizes methodology related to specific classes of vehicle routing problems and, since vehicle routing is used as a benchmark for all new solution techniques, contains a complete overview of current solutions to combinatorial optimization problems. It also includes several chapters on important and emerging applications, such as disaster relief and green vehicle routing.

Author: Shyamali Ghosh
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 30

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Book Description
In this contribution, for the first time, an effcient model of multi-objective product blending fixed-charge transportation problem with truck load constraints through transfer station is formulated.

Author: Marlin Wolf Ulmer
Publisher: Springer
ISBN: 3319555111
Category : Business & Economics
Languages : en
Pages : 209

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Book Description
This book provides a straightforward overview for every researcher interested in stochastic dynamic vehicle routing problems (SDVRPs). The book is written for both the applied researcher looking for suitable solution approaches for particular problems as well as for the theoretical researcher looking for effective and efficient methods of stochastic dynamic optimization and approximate dynamic programming (ADP). To this end, the book contains two parts. In the first part, the general methodology required for modeling and approaching SDVRPs is presented. It presents adapted and new, general anticipatory methods of ADP tailored to the needs of dynamic vehicle routing. Since stochastic dynamic optimization is often complex and may not always be intuitive on first glance, the author accompanies the ADP-methodology with illustrative examples from the field of SDVRPs. The second part of this book then depicts the application of the theory to a specific SDVRP. The process starts from the real-world application. The author describes a SDVRP with stochastic customer requests often addressed in the literature, and then shows in detail how this problem can be modeled as a Markov decision process and presents several anticipatory solution approaches based on ADP. In an extensive computational study, he shows the advantages of the presented approaches compared to conventional heuristics. To allow deep insights in the functionality of ADP, he presents a comprehensive analysis of the ADP approaches.

Author: John R. Birge
Publisher: Springer Science & Business Media
ISBN: 0387226184
Category : Mathematics
Languages : en
Pages : 427

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Book Description
This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.

Author: José-Luis Verdegay
Publisher: Springer
ISBN: 3540364617
Category : Mathematics
Languages : en
Pages : 357

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Book Description
The aim of this volume is to show how Fuzzy Sets and Systems can help to provide robust and adaptive heuristic optimization algorithms in a variety of situations. The book presents the state of the art and gives a broad overview on the real practical applications that Fuzzy Sets, based on heuristic algorithms, have.

Author: Dr. Mohd. B. Pathan
Publisher: Lulu.com
ISBN: 0359751717
Category : Education
Languages : en
Pages : 174

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Book Description
The Operations Research (OR) is used to analyze real life descriptive problems. It helps to represent real problems related to an organization/industry/institute etc. in terms of mathematical form. The progress of any organization / industry is based on appropriate decision related to man-power management, time-management, purchasing of raw material, shipment of manufactured goods, etc. Therefore, the decision making process plays vital role for the progress of any organization. The decision can be made by judgment or by using past experience regarding behavior of system, which is not possible in all situations. Hence, it becomes necessary to take appropriate decisions based on some systematic mathematical technique which is termed as "Operations Research (OR)".

Author: Xin Yao
Publisher: Springer Science & Business Media
ISBN: 3540230920
Category : Computers
Languages : en
Pages : 1204

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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Parallel Problem Solving from Nature, PPSN 2004, held in Birmingham, UK, in September 2004. The 119 revised full papers presented were carefully reviewed and selected from 358 submissions. The papers address all current issues in biologically inspired computing; they are organized in topical sections on theoretical and foundational issues, new algorithms, applications, multi-objective optimization, co-evolution, robotics and multi-agent systems, and learning classifier systems and data mining.

Author: Cynthia Barnhart
Publisher: Elsevier
ISBN: 0080467431
Category : Psychology
Languages : en
Pages : 796

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Book Description
This book contains eleven chapters describing some of the most recent methodological operations research developments in transportation. It is structured around the main transportation modes, and each chapter is written by a group of well-recognized researchers. Because of the major impact of operations research methods in the field of air transportation over the past forty years, it is befitting to open the book with a chapter on airline operations management. This book will prove useful to researchers, students, and practitioners in transportation and will stimulate further research in this rich and fascinating area. - Volume 14 examines transport and its relationship with operations and management science - 11 chapters cover the most recent research developments in transportation - Focuses on main transportation modes-air travel, automobile, public transit, maritime transport, and more

Author: Dimitri Bertsekas
Publisher: Athena Scientific
ISBN: 1886529078
Category : Computers
Languages : en
Pages : 498

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Book Description
The purpose of this book is to develop in greater depth some of the methods from the author's Reinforcement Learning and Optimal Control recently published textbook (Athena Scientific, 2019). In particular, we present new research, relating to systems involving multiple agents, partitioned architectures, and distributed asynchronous computation. We pay special attention to the contexts of dynamic programming/policy iteration and control theory/model predictive control. We also discuss in some detail the application of the methodology to challenging discrete/combinatorial optimization problems, such as routing, scheduling, assignment, and mixed integer programming, including the use of neural network approximations within these contexts. The book focuses on the fundamental idea of policy iteration, i.e., start from some policy, and successively generate one or more improved policies. If just one improved policy is generated, this is called rollout, which, based on broad and consistent computational experience, appears to be one of the most versatile and reliable of all reinforcement learning methods. In this book, rollout algorithms are developed for both discrete deterministic and stochastic DP problems, and the development of distributed implementations in both multiagent and multiprocessor settings, aiming to take advantage of parallelism. Approximate policy iteration is more ambitious than rollout, but it is a strictly off-line method, and it is generally far more computationally intensive. This motivates the use of parallel and distributed computation. One of the purposes of the monograph is to discuss distributed (possibly asynchronous) methods that relate to rollout and policy iteration, both in the context of an exact and an approximate implementation involving neural networks or other approximation architectures. Much of the new research is inspired by the remarkable AlphaZero chess program, where policy iteration, value and policy networks, approximate lookahead minimization, and parallel computation all play an important role.