Linear Multiobjective Programming
Linear Multiobjective Programming

Author: M. Zeleny

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 233

ISBN-13: 3642808085

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1.1. The origin of the multiobjective problem and a short historical review The continuing search for a discovery of theories, tools and c- cepts applicable to decision-making processes has increased the complexity of problems eligible for analytical treatment. One of the more pertinent criticisms of current decision-making theory and practice is directed against the traditional approximation of multiple goal behavior of men and organizations by single, technically-convenient criterion. Reins- tementof the role of human judgment in more realistic, multiple goal se,ttings has been one of the ma~or recent developments in the literature. Consider the following simplified problem. There is a large number of people to be transported daily between two industrial areas and their adjacent residential areas. Given some budgetary and technological c- straints we would like to determine optimal transportation modes as well as the number of units of each to be scheduled for service. What is the optimal solution? Are we interested in the cheapest transportation? Do we want the fastest, the safest, the cleanest, the most profitable, the most durable? There are many criteria which are to be considered: travel times, consumer's cost, construction cost, operating cost, expected fatalities and injuries, probability of delays, etc.

Multiobjective Linear Programming
Multiobjective Linear Programming

Author: Dinh The Luc

Publisher: Springer

Published: 2015-07-31

Total Pages: 328

ISBN-13: 3319210912

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This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineering or operations research involve conflicting criteria and therefore it is more convenient to formulate them as multicriteria optimization models, the solution concepts and methods of which cannot be treated using traditional mathematical programming approaches.

Multiobjective Linear and Integer Programming
Multiobjective Linear and Integer Programming

Author: Carlos Henggeler Antunes

Publisher: Springer

Published: 2016-04-08

Total Pages: 216

ISBN-13: 331928746X

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This book opens the door to multiobjective optimization for students in fields such as engineering, management, economics and applied mathematics. It offers a comprehensive introduction to multiobjective optimization, with a primary emphasis on multiobjective linear programming and multiobjective integer/mixed integer programming. A didactic book, it is mainly intended for undergraduate and graduate students, but can also be useful for researchers and practitioners. Further, it is accompanied by an interactive software package - developed by the authors for Windows platforms - which can be used for teaching and decision-making support purposes in multiobjective linear programming problems. Thus, besides the textbook’s coverage of the essential concepts, theory and methods, complemented with illustrative examples and exercises, the computational tool enables students to experiment and enhance their technical skills, as well as to capture the essential characteristics of real-world problems.

Multiobjective Programming and Planning
Multiobjective Programming and Planning

Author: Jared L. Cohon

Publisher: Courier Corporation

Published: 2013-01-18

Total Pages: 368

ISBN-13: 048615307X

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This text takes a broad view of multiobjective programming, emphasizing the methods most useful for continuous problems. It reviews methods in the context of public decision-making problems. 1978 edition.

Nonlinear Multiobjective Optimization
Nonlinear Multiobjective Optimization

Author: Kaisa Miettinen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 304

ISBN-13: 1461555639

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Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making (MCDM) problems. So far, these types of problems have typically been modelled and solved by means of linear programming. However, many real-life phenomena are of a nonlinear nature, which is why we need tools for nonlinear programming capable of handling several conflicting or incommensurable objectives. In this case, methods of traditional single objective optimization and linear programming are not enough; we need new ways of thinking, new concepts, and new methods - nonlinear multiobjective optimization. Nonlinear Multiobjective Optimization provides an extensive, up-to-date, self-contained and consistent survey, review of the literature and of the state of the art on nonlinear (deterministic) multiobjective optimization, its methods, its theory and its background. The amount of literature on multiobjective optimization is immense. The treatment in this book is based on approximately 1500 publications in English printed mainly after the year 1980. Problems related to real-life applications often contain irregularities and nonsmoothnesses. The treatment of nondifferentiable multiobjective optimization in the literature is rather rare. For this reason, this book contains material about the possibilities, background, theory and methods of nondifferentiable multiobjective optimization as well. This book is intended for both researchers and students in the areas of (applied) mathematics, engineering, economics, operations research and management science; it is meant for both professionals and practitioners in many different fields of application. The intention has been to provide a consistent summary that may help in selecting an appropriate method for the problem to be solved. It is hoped the extensive bibliography will be of value to researchers.

Linear Multiobjective Programming
Linear Multiobjective Programming

Author: Milan Zeleny

Publisher: Springer

Published: 1974

Total Pages: 244

ISBN-13:

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1.1. The origin of the multiobjective problem and a short historical review The continuing search for a discovery of theories, tools and c- cepts applicable to decision-making processes has increased the complexity of problems eligible for analytical treatment. One of the more pertinent criticisms of current decision-making theory and practice is directed against the traditional approximation of multiple goal behavior of men and organizations by single, technically-convenient criterion. Reins- tementof the role of human judgment in more realistic, multiple goal se,ttings has been one of the mãor recent developments in the literature. Consider the following simplified problem. There is a large number of people to be transported daily between two industrial areas and their adjacent residential areas. Given some budgetary and technological c- straints we would like to determine optimal transportation modes as well as the number of units of each to be scheduled for service. What is the optimal solution? Are we interested in the cheapest transportation? Do we want the fastest, the safest, the cleanest, the most profitable, the most durable? There are many criteria which are to be considered: travel times, consumer's cost, construction cost, operating cost, expected fatalities and injuries, probability of delays, etc.

Linear and Multiobjective Programming with Fuzzy Stochastic Extensions
Linear and Multiobjective Programming with Fuzzy Stochastic Extensions

Author: Masatoshi Sakawa

Publisher: Springer Science & Business Media

Published: 2013-11-29

Total Pages: 347

ISBN-13: 1461493994

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Although several books or monographs on multiobjective optimization under uncertainty have been published, there seems to be no book which starts with an introductory chapter of linear programming and is designed to incorporate both fuzziness and randomness into multiobjective programming in a unified way. In this book, five major topics, linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, are presented in a comprehensive manner. Especially, the last four topics together comprise the main characteristics of this book, and special stress is placed on interactive decision making aspects of multiobjective programming for human-centered systems in most realistic situations under fuzziness and/or randomness. Organization of each chapter is briefly summarized as follows: Chapter 2 is a concise and condensed description of the theory of linear programming and its algorithms. Chapter 3 discusses fundamental notions and methods of multiobjective linear programming and concludes with interactive multiobjective linear programming. In Chapter 4, starting with clear explanations of fuzzy linear programming and fuzzy multiobjective linear programming, interactive fuzzy multiobjective linear programming is presented. Chapter 5 gives detailed explanations of fundamental notions and methods of stochastic programming including two-stage programming and chance constrained programming. Chapter 6 develops several interactive fuzzy programming approaches to multiobjective stochastic programming problems. Applications to purchase and transportation planning for food retailing are considered in Chapter 7. The book is self-contained because of the three appendices and answers to problems. Appendix A contains a brief summary of the topics from linear algebra. Pertinent results from nonlinear programming are summarized in Appendix B. Appendix C is a clear explanation of the Excel Solver, one of the easiest ways to solve optimization problems, through the use of simple examples of linear and nonlinear programming.

Multiobjective Optimization
Multiobjective Optimization

Author: Jürgen Branke

Publisher: Springer

Published: 2008-10-18

Total Pages: 481

ISBN-13: 3540889086

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Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

An Introduction to Linear Programming and Game Theory
An Introduction to Linear Programming and Game Theory

Author: Paul R. Thie

Publisher: John Wiley & Sons

Published: 2011-09-15

Total Pages: 476

ISBN-13: 1118165454

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Praise for the Second Edition: "This is quite a well-done book: very tightly organized, better-than-average exposition, and numerous examples, illustrations, and applications." —Mathematical Reviews of the American Mathematical Society An Introduction to Linear Programming and Game Theory, Third Edition presents a rigorous, yet accessible, introduction to the theoretical concepts and computational techniques of linear programming and game theory. Now with more extensive modeling exercises and detailed integer programming examples, this book uniquely illustrates how mathematics can be used in real-world applications in the social, life, and managerial sciences, providing readers with the opportunity to develop and apply their analytical abilities when solving realistic problems. This Third Edition addresses various new topics and improvements in the field of mathematical programming, and it also presents two software programs, LP Assistant and the Solver add-in for Microsoft Office Excel, for solving linear programming problems. LP Assistant, developed by coauthor Gerard Keough, allows readers to perform the basic steps of the algorithms provided in the book and is freely available via the book's related Web site. The use of the sensitivity analysis report and integer programming algorithm from the Solver add-in for Microsoft Office Excel is introduced so readers can solve the book's linear and integer programming problems. A detailed appendix contains instructions for the use of both applications. Additional features of the Third Edition include: A discussion of sensitivity analysis for the two-variable problem, along with new examples demonstrating integer programming, non-linear programming, and make vs. buy models Revised proofs and a discussion on the relevance and solution of the dual problem A section on developing an example in Data Envelopment Analysis An outline of the proof of John Nash's theorem on the existence of equilibrium strategy pairs for non-cooperative, non-zero-sum games Providing a complete mathematical development of all presented concepts and examples, Introduction to Linear Programming and Game Theory, Third Edition is an ideal text for linear programming and mathematical modeling courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for professionals who use game theory in business, economics, and management science.

Fuzzy Stochastic Multiobjective Programming
Fuzzy Stochastic Multiobjective Programming

Author: Masatoshi Sakawa

Publisher: Springer

Published: 2013-04-19

Total Pages: 0

ISBN-13: 9781461428060

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Although studies on multiobjective mathematical programming under uncertainty have been accumulated and several books on multiobjective mathematical programming under uncertainty have been published (e.g., Stancu-Minasian (1984); Slowinski and Teghem (1990); Sakawa (1993); Lai and Hwang (1994); Sakawa (2000)), there seems to be no book which concerns both randomness of events related to environments and fuzziness of human judgments simultaneously in multiobjective decision making problems. In this book, the authors are concerned with introducing the latest advances in the field of multiobjective optimization under both fuzziness and randomness on the basis of the authors’ continuing research works. Special stress is placed on interactive decision making aspects of fuzzy stochastic multiobjective programming for human-centered systems under uncertainty in most realistic situations when dealing with both fuzziness and randomness. Organization of each chapter is briefly summarized as follows: Chapter 2 is devoted to mathematical preliminaries, which will be used throughout the remainder of the book. Starting with basic notions and methods of multiobjective programming, interactive fuzzy multiobjective programming as well as fuzzy multiobjective programming is outlined. In Chapter 3, by considering the imprecision of decision maker’s (DM’s) judgment for stochastic objective functions and/or constraints in multiobjective problems, fuzzy multiobjective stochastic programming is developed. In Chapter 4, through the consideration of not only the randomness of parameters involved in objective functions and/or constraints but also the experts’ ambiguous understanding of the realized values of the random parameters, multiobjective programming problems with fuzzy random variables are formulated. In Chapter 5, for resolving conflict of decision making problems in hierarchical managerial or public organizations where there exist two DMs who have different priorities in making decisions, two-level programming problems are discussed. Finally, Chapter 6 outlines some future research directions.