Multiple Criteria Decision Making By Multiobjective Optimization

This textbook approaches optimization from a multi-aspect, multi-criteria perspective. By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the limits and oversimplifications that can come with optimization models with one criterion. The book is presented in a concise form, addressing how to solve decision problems in sequences of intelligence, modelling, choice and review phases, often iterated, to identify the most preferred decision variant. The approach taken is human-centric, with the user taking the final decision is a sole and sovereign actor in the decision making process. To ensure generality, no assumption about the Decision Maker preferences or behavior is made. The presentation of these concepts is illustrated by numerous examples, figures, and problems to be solved with the help of downloadable spreadsheets. This electronic companion contains models of problems to be solved built in Excel spreadsheet files. Optimization models are too often oversimplifications of decision problems met in practice. For instance, modeling company performance by an optimization model in which the criterion function is short-term profit to be maximized, does not fully reflect the essence of business management. The company’s managing staff is accountable not only for operational decisions, but also for actions which shall result in the company ability to generate a decent profit in the future. This calls for management decisions and actions which ensure short-term profitability, but also maintaining long-term relations with clients, introducing innovative products, financing long-term investments, etc. Each of those additional, though indispensable actions and their effects can be modeled separately, case by case, by an optimization model with a criterion function adequately selected. However, in each case the same set of constraints represents the range of company admissible actions. The aim and the scope of this textbook is to present methodologies and methods enabling modeling of such actions jointly.

- Collection of results of multicriteria optimization, including nonlinear, linear and combinatorial optimization problems - Includes numerous illustrations, examples and problems

Multi-Criteria Decision Making (MCDM) has been one of the fastest growing problem areas in many disciplines. The central problem is how to evaluate a set of alternatives in terms of a number of criteria. Although this problem is very relevant in practice, there are few methods available and their quality is hard to determine. Thus, the question `Which is the best method for a given problem?' has become one of the most important and challenging ones. This is exactly what this book has as its focus and why it is important. The author extensively compares, both theoretically and empirically, real-life MCDM issues and makes the reader aware of quite a number of surprising `abnormalities' with some of these methods. What makes this book so valuable and different is that even though the analyses are rigorous, the results can be understood even by the non-specialist. Audience: Researchers, practitioners, and students; it can be used as a textbook for senior undergraduate or graduate courses in business and engineering.

This book is an outgrowth of formal graduate courses in multiple-criteria decision making (MCDM) that the author has taught at the University of Rochester, University of Texas at Austin, and University of Kansas since 1972. The purpose is, on one hand, to offer the reader an integral and systematic view of various concepts and techniques in MCDM at an "introductory" level, and, on the other hand, to provide a basic conception of the human decision mechanism, which may improve our ability to apply the techniques we have learned and may broaden our llJ.ind for modeling human decision making. The book is written with a goal in mind that the reader should be able to assimilate and benefit from most of the concepts in the book if he has the mathematical maturity equivalent to a course in operations research or optimiz ation theory. Good training in linear and nonlinear programming is sufficient to digest, perhaps easily, most of the concepts in the book.

This volume is devoted to models and methods in multiple objectives decision making. The importance of the multiple dimensions of decision making was first recognised during the 1960s and since then progress has been made in that theoretical or application oriented contributions may now be categorized under two main headings:- Multiattribute Decision Making (MADM) which concerns the sorting, the ranking or the evaluation of objects of choice according to several criteria and Multiobjective Decision Making (MODM) which deals with the vector optimization in mathematical programming. The above are also presented in the context of various applications, namely banking, environment, health, manpower, media, portfolio and traffic control, resulting in a book for a wide variety of readers.

The generalized area of multiple criteria decision making (MCDM) can be defined as the body of methods and procedures by which the concern for multiple conflicting criteria can be formally incorporated into the analytical process. MCDM consists mostly of two branches, multiple criteria optimization and multi-criteria decision analysis (MCDA). While MCDA is typically concerned with multiple criteria problems that have a small number of alternatives often in an environment of uncertainty (location of an airport, type of drug rehabilitation program), multiple criteria optimization is typically directed at problems formulated within a mathematical programming framework, but with a stack of objectives instead of just one (river basin management, engineering component design, product distribution). It is about the most modern treatment of multiple criteria optimization that this book is concerned. I look at this book as a nicely organized and well-rounded presentation of what I view as ”new wave” topics in multiple criteria optimization. Looking back to the origins of MCDM, most people agree that it was not until about the early 1970s that multiple criteria optimization c- gealed as a field. At this time, and for about the following fifteen years, the focus was on theories of multiple objective linear programming that subsume conventional (single criterion) linear programming, algorithms for characterizing the efficient set, theoretical vector-maximum dev- opments, and interactive procedures.

It was a great honor and privilege to organize the Tenth International Conference on Multiple Criteria Decision Making at Taipei, Taiwan, July 19-24, 1992. Accompanying this unique honor and privilege there was a series of complex, challenging problems. Each of them involved multiple criteria, fuzziness, uncertainty, unknown yet dynamic changes. The problem sometimes cost us sleep because we wanted to do the very best job, but in reality it seemed to be impossible. The following are the main goals of the organization committee: (i) inviting all prominent and distinguished MCDM scholars around the world to participate in the conference and to present their up-to-date research results, (ii) providing financial aid and hospitality so that each invited speaker can have free room and board at a five star hotel, (iii) creating an environment so that all participants can freely exchange their ideas, and build friendships around the world. Due to the enthusiastic participation of the prominent scholars, the generous support of the Taiwan government, universities, the Industrial leaders and nonprofit foundations, and the active problem solving attitude and doing of the organizational committee and the Habitual Domain (HD) club, the conference was a great success.

Ch. 1. The early history of MCDM -- ch. 2. MCDM developments in the 1970s -- ch. 3. MCDM developments in the 1980s -- ch. 4. MCDM developments in the 1990s and beyond -- ch. 5. MCDM conferences -- ch. 6. MCDM society traditions -- ch. 7. Awards and presidents -- ch. 8. Biographies of leading MCDM scholars -- ch. 9. Conclusion