Multi-Criteria Decision Making in Industrial Engineering

A Special Issue of the Journal
Computers and Industrial Engineering
Vol. 37, No. 3, 1999
(Published in April 17, 2000)
Evangelos Triantaphyllou and Gerald W. Evans,     Guest Editors
PREFACE (pages 505-506)

Dedicated to the Memory of the late Dr. Hamed Kamal Eldin, Founding Editor of the Journal Computers & Industrial Engineering


      One of the core areas of industrial engineering practice and research is that of decision making, in particular multi- criteria/multi-objective decision making. This is a very broad and vibrant subject to be covered in a single Special Issue. Thus, this issue presents a collection of ten papers that are representative to some of the most vital areas within the multi- criteria/multi-objective decision making domain. These papers range from very practical to foundation ones from the theoretical point of view.

      The papers in this special issue can be grouped into a number of sub-areas. The first two papers refer to multi- criteria decision making (MCDM). In this context the decision maker is given a collection of alternatives and it is required to evaluate them in terms of a number of decision criteria. The first paper was written by Poh and Ang and presents a practical application of the analytic hierarchy process (AHP) to an acute problem in Singapore. This is a very complex problem that involves environmental, economic and technological issues. The second paper was written by Choo, Schoner, and Wedley and addresses some theoretical issues on the interpretation of the criteria weights in an MCDM problem. These authors reveal a number of counter-intuitive issues on a subject that is both very critical and also widely misunderstood by many decision makers and researchers.

      The next three papers are related to various problems that involve optimization in terms of two criteria (bicriteria optimization). The paper by Kolli and Evans describes an application of multiple objective optimization for planning franchise expansion. It describes both the theoretical foundations of this important problem and also provides a wide empirical study on simulated test problems. The second paper in this group was written by Liu and Dauer and describes the analysis of alternatives in terms of two competing criteria (bicriteria optimization). It describes some diverse and very prominent classification problems that are examined in terms of bicriteria optimization models. It also provides both theoretical and empirical information on the models analyzed. The third paper was written by Melachrinoudis and describes a bicriteria optimization model for dealing with the location problem of semi- obnoxious facilities. It provides a mechanism for balancing the competing factors that often exist in locating such facilities. It also provides an excellent algorithmic approach for dealing with such models as effectively as possible.

      The third group is comprised by the last four papers in this issue. The first paper in this group was written by W. Ogryczak and deals with a location problem. In this problem it is required to locate a given number of facilities that will serve some clients. This is formulated as a multi-objective decision making problem. Unlike previous approaches to this problem, the solution approach proposed here attempts to minimize the entire distribution of the distances involved. It does so by employing an interactive step that identifies efficient solutions. This paper provides both theoretical and empirical results on the proposed algorithm.

      The second paper in the last group was written by Susan Li and it deals with game theory with multiple decision makers. It formulates this situation as a multi-objective decision making problem and next it attempts to identify efficient solutions. Applications include the modeling of the competitive relations that exist between consumers and suppliers or the investment decisions (portfolio composition) made by shareholders in the stock market. The proposed approach provides for ways to identify efficient solutions for such problems.

      The third paper in this group was written by Trafalis, Mishina and Foote and it also deals with multi-objective programming. However, unlike the previous approaches, now the data are stochastic. Thus, one of its applications is in production control. Their approach incorporates an interactive step for eliciting additional information from the decision maker(s). It also uses an ellipsoid interior point method to relatively easily identify a wide range of possible efficient solutions. The last paper in this group was also written by Trafalis with Alkahtani as the co-author. This paper is a rather theoretical one. It presents the use of an interior point algorithm for solving multi-objective linear programming problems (like some of the ones presented earlier). The authors also provide some empirical results on the performance of their algorithm on some test problems.

      Finally, it should be stated here that the Editors are immensely grateful to the authors of these papers for their patience and their perseverance in helping to achieve the high standards of these papers. The Editors would have never achieved their goals without the assistance of the reviewers whose contributions are also acknowledged with gratitude here. Finally, they would like to express their many thanks to the new Chief Editor Dr. Mohamed I. Dessouky for all his assistance.

                                                Evangelos Triantaphyllou and Gerald W. Evans,     Guest Editors

                                                October 1999

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