Fuzzy Sets and Interactive Multiobjective Optimization

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Release : 2013-11-21
Genre : Mathematics
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Book Rating : 334/5 ( reviews)

Fuzzy Sets and Interactive Multiobjective Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Sets and Interactive Multiobjective Optimization write by Masatoshi Sakawa. This book was released on 2013-11-21. Fuzzy Sets and Interactive Multiobjective Optimization available in PDF, EPUB and Kindle. The main characteristics of the real-world decision-making problems facing humans today are multidimensional and have multiple objectives including eco nomic, environmental, social, and technical ones. Hence, it seems natural that the consideration of many objectives in the actual decision-making process re quires multiobjective approaches rather than single-objective. One ofthe major systems-analytic multiobjective approaches to decision-making under constraints is multiobjective optimization as a generalization of traditional single-objective optimization. Although multiobjective optimization problems differ from single objective optimization problems only in the plurality of objective functions, it is significant to realize that multiple objectives are often noncom mensurable and conflict with each other in multiobjective optimization problems. With this ob servation, in multiobjective optimization, the notion of Pareto optimality or effi ciency has been introduced instead of the optimality concept for single-objective optimization. However, decisions with Pareto optimality or efficiency are not uniquely determined; the final decision must be selected from among the set of Pareto optimal or efficient solutions. Therefore, the question is, how does one find the preferred point as a compromise or satisficing solution with rational pro cedure? This is the starting point of multiobjective optimization. To be more specific, the aim is to determine how one derives a compromise or satisficing so lution of a decision maker (DM), which well represents the subjective judgments, from a Pareto optimal or an efficient solution set.

Large Scale Interactive Fuzzy Multiobjective Programming

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Release : 2012-12-06
Genre : Business & Economics
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Book Rating : 518/5 ( reviews)

Large Scale Interactive Fuzzy Multiobjective Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Large Scale Interactive Fuzzy Multiobjective Programming write by Masatoshi Sakawa. This book was released on 2012-12-06. Large Scale Interactive Fuzzy Multiobjective Programming available in PDF, EPUB and Kindle. Simultaneous considerations of multiobjectiveness, fuzziness and block angular structures involved in the real-world decision making problems lead us to the new field of interactive multiobjective optimization for large scale programming problems under fuzziness. The aim of this book is to introduce the latest advances in the new field of interactive multiobjective optimization for large scale programming problems under fuzziness on the basis of the author's continuing research. Special stress is placed on interactive decision making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The book is intended for graduate students, researchers and practitioners in the fields of operations research, industrial engineering, management science and computer science.

Interactive Fuzzy Optimization

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Release : 2012-12-06
Genre : Business & Economics
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Book Rating : 002/5 ( reviews)

Interactive Fuzzy Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Interactive Fuzzy Optimization write by Mario Fedrizzi. This book was released on 2012-12-06. Interactive Fuzzy Optimization available in PDF, EPUB and Kindle. The title of this book seems to indicate that the volume is dedicated to a very specialized and narrow area, i. e. , to the relationship between a very special type of optimization and mathematical programming. The contrary is however true. Optimization is certainly a very old and classical area which is of high concern to many disciplines. Engineering as well as management, politics as well as medicine, artificial intelligence as well as operations research, and many other fields are in one way or another concerned with optimization of designs, decisions, structures, procedures, or information processes. It is therefore not surprising that optimization has not grown in a homogeneous way in one discipline either. Traditionally, there was a distinct difference between optimization in engineering, optimization in management, and optimization as it was treated in mathematical sciences. However, for the last decades all these fields have to an increasing degree interacted and contributed to the area of optimization or decision making. In some respects, new disciplines such as artificial intelligence, descriptive decision theory, or modern operations research have facilitated, or even made possible the interaction between the different classical disciplines because they provided bridges and links between areas which had been developing and applied quite independently before. The development of optimiiation over the last decades can best be appreciated when looking at the traditional model of optimization. For a well-structured, Le.

Genetic Algorithms and Fuzzy Multiobjective Optimization

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Release : 2002
Genre : Business & Economics
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Book Rating : 527/5 ( reviews)

Genetic Algorithms and Fuzzy Multiobjective Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Genetic Algorithms and Fuzzy Multiobjective Optimization write by Masatoshi Sakawa. This book was released on 2002. Genetic Algorithms and Fuzzy Multiobjective Optimization available in PDF, EPUB and Kindle. Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a wide range of actual real world applications. The theoretical material and applications place special stress on interactive decision-making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The intended readers of this book are senior undergraduate students, graduate students, researchers, and practitioners in the fields of operations research, computer science, industrial engineering, management science, systems engineering, and other engineering disciplines that deal with the subjects of multiobjective programming for discrete or other hard optimization problems under fuzziness. Real world research applications are used throughout the book to illustrate the presentation. These applications are drawn from complex problems. Examples include flexible scheduling in a machine center, operation planning of district heating and cooling plants, and coal purchase planning in an actual electric power plant.

Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty

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Release : 2012-12-06
Genre : Business & Economics
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Book Rating : 11X/5 ( reviews)

Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty write by Shi-Yu Huang. This book was released on 2012-12-06. Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty available in PDF, EPUB and Kindle. Operations Research is a field whose major contribution has been to propose a rigorous fonnulation of often ill-defmed problems pertaining to the organization or the design of large scale systems, such as resource allocation problems, scheduling and the like. While this effort did help a lot in understanding the nature of these problems, the mathematical models have proved only partially satisfactory due to the difficulty in gathering precise data, and in formulating objective functions that reflect the multi-faceted notion of optimal solution according to human experts. In this respect linear programming is a typical example of impressive achievement of Operations Research, that in its detenninistic fonn is not always adapted to real world decision-making : everything must be expressed in tenns of linear constraints ; yet the coefficients that appear in these constraints may not be so well-defined, either because their value depends upon other parameters (not accounted for in the model) or because they cannot be precisely assessed, and only qualitative estimates of these coefficients are available. Similarly the best solution to a linear programming problem may be more a matter of compromise between various criteria rather than just minimizing or maximizing a linear objective function. Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.