Interactive Fuzzy Optimization

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.

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.

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.

This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.

Optimization is an extremely important area in science and technology which provides powerful and useful tools and techniques for the formulation and solution of a multitude of problems in which we wish, or need, to to find a best possible option or solution. The volume is divided into a coupe of parts which present various aspects of fuzzy optimization, some related more general issues, and applications.

This potent area of technology allows us to formulate and solve a multitude of problems. Written by leading experts, this overview covers a number of aspects of fuzzy optimization, some related general issues, and various applications of this powerful tool.

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.