NEW BOOK!
TABLE OF CONTENTS
by K.L. Poh and B.W. Ang (See Abstract) by Eng U. Choo, Bertram Schoner, and William C. Wedley (See Abstract) A Multiple Objective Integer Programming Programming Approach For Planning Franchise Expansion by Sai Kolli and Gerald W. Evans (See Abstract) Bicriteria Programming With Several Modern Applications by Yi-Hsin Liu and Jerald P. Dauer (See Abstract) Bicriteria Location of a Semi-Obnoxius Facility by Emanuel Melachrinoudis (See Abstract) On the Distribution Approach to Location Problems by Wlodzimierz Ogryczak (See Abstract) Interactive Strategy Sets in Multiple Payoff Games by Susan X. Li (See Abstract) An Interior Multi-Objective Programming Approach For Production Planning With Uncertain Information by Theodore B. Trafalis, Tsutomu Mishina, and Bobbie L. Foote (See Abstract) An Interactive Analytic Center Tradeoff Cutting Plane Algorithm For Multi-Objective Linear Programming by Theodore B. Trafalis and Rashid M. Alkahtani (See Abstract)
ABSTRACTS:
Computers & IE, Vol. 37, No. 3, pp. 507-525, 1999. by K.L. Poh and B.W. Ang Department of Industrial and Systems Engineering National University of Singapore 10 Kent Ridge Crescent SINGAPORE 119260 ABSTRACT: A comprehensive study of alternative fuels for land transportation in Singapore is carried out. A multiple attribute analysis is used to identify a number of fuel options for possible future use. An AHP analysis is performed to evaluate four possible plans or scenarios. The preferred plan, however, deviates from the most likely future scenario and an iterative forward and backward AHP planning process is used to identify and evaluate a set of policies, which may be used to reduce the gap. KEY WORDS: Multi-Criteria Decision Making (MCDM), the Analytic Hierarchy Process (AHP), Transportation Fuels. 
Computers & IE, Vol. 37, No. 3, pp. 527-541, 1999. by Eng U. Choo, Bertram Schoner and William C. Wedley Faculty of Business Administration Simon Fraser University British Columbia CANADA ABSTRACT: Multi-criteria decision-making models are characterized by the need to evaluate a finite set of alternatives with respect to multiple criteria. The criteria weights in different aggregation rules have different interpretation and implications, which have been misunderstood and neglected by many decision-makers and researchers. By analyzing the aggregation rules, identifying partial values, specifying explicit measurement units and explicating direct statements of pairwise comparisons of preferences, we identify several plausible interpretations of criteria weights and their appropriate roles in different multi-criteria decision making models. The underlying issues of scale validity, commensurability, criteria importance and rank consistency are examined. KEY WORDS: Criteria Weights, Preferences, Multi-Criteria Decision Making (MCDM), Multi-Attribute Utility Theory (MAUT), the Analytic Hierarchy Process (AHP).
Computers & IE, Vol. 37, No. 3, pp. 543-561, 1999. by Sai Kolli 1 and Gerald W. Evans 2 1: Eagle Finance Department American Airlines P.O. Box 619616, MD 5494 Dallas/Fort worth Int'l Airport, TX 76155 U.S.A. 2: Department of Industrial Engineering University of Louisville Louisville, KY 40292 U.S.A. ABSTRACT: The number and configuration of franchise outlets in a market defines the distribution of a franchise company. The introduction of new franchise outlets contributes to conflict between the franchise and franchiser over the degree of market penetration. The selection of sites for new franchises is an important factor in the long-tern profitability of many types of franchises. This selection process requires consideration of objectives of the franchisee and franchiser, which are often conflicting in nature. This paper deals with the problem of locating new franchises in an existing franchise network using multiple objective integer programming models and methods. KEY WORDS: Facility Location, Marketing, Integer Programming, Multiple Objective Optimization.
Computers & IE, Vol. 37, No. 3, pp. 563-580, 1999. by Yi-Hsin Liu 1 and Jerald P. Dauer 2 1: Department of Mathematics University of Nebraska at Omaha Omaha, Nebraska 68182 U.S.A. 2: Department of Mathematics University of Tennessee at Chattanooga Chattanooga, Tennessee 37403 U.S.A. ABSTRACT: Applications of bicriteria linear programming in classification and selections are discussed. The use of the bicriteria classification and selection model is presented in applications of genotype selection in the corn breeding problem and feature selection in a pattern recognition problem. KEY WORDS: Bicriteria Programming, Genotype Selection, Pattern Recognition, Multi-Criteria Optimization.
Computers & IE, Vol. 37, No. 3, pp. 581-593, 2000. by Emanuel Melachrinoudis Dept. Of Mechanical, Industrial & Manufacturing Engineering Northeastern University Boston, MA 02115 U.S.A. ABSTRACT: The problem of locating a new semi-obnoxious facility in an existing layout is considered. The facility interacts with the existing facilities, so that on one hand, it is desired to be placed close to them in order to minimize total transportation cost, but on the other hand it is not desired to be placed too close to them because it has certain undesirable effects. For this problem, a maximin-minisum bicriteria location model with rectilinear distances is developed. The resulting nonconvex bicriteria problem is decomposed into a series of linear bicriteria problems which are solved by an adaptation of the Fourier-Motzkin Elimination Method. An algorithm that constructs the entire nondominated and efficient sets is presented and it is illustrated in an example problem. KEY WORDS: Facility Location, Minisum, Maximin, Bicriteria Optimization, Fourier-Motzkin Elimination.
Computers & IE, Vol. 37, No. 3, pp. 595-612, 1999. by Wlodzimierz Ogryczak Warsaw University Department of Mathematics and Computer Science 02-097 Warsaw POLAND ABSTRACT: While making location decisions, the distribution of travel distances among the service recipients (clients) is an important issue. It is usually tackled with the minimax (center) or the minisum (median) solution concepts. Both concepts minimize only simple scalar characteristics of the distribution: the maximal distance and the average distance, respectively. In this paper all the distances for the individual clients are considered as a set of multiple uniform criteria to be minimized. This results in a multiple criteria model taking into account the entire distribution of distances. Our analysis of the multiple criteria problem focuses on the symmetrically efficient solutions which comply with minimization of distances, as well as with impartial consideration of the clients. Various solution concepts generating symmetrically efficient location patterns are analyzed. Finally, the reference distribution approach is developed as an interactive technique, which enables to identify a satisfactory symmetrically efficient location pattern by evolving a reference (target) distribution of distances. KEY WORDS: Location Problems, Multiple Criteria, Symmetric Efficiency, Interactive Methods, Reference Point.
Computers & IE, Vol. 37, No. 3, pp. 613-630, 1999. by Susan X. Li School of Management and Business Administration Adelphi University Garden City, NY 11530 U.S.A. ABSTRACT: In game theory, it is usually assumed that each player has only one payoff function and the strategy set of the game is composed of the topological product of individual players' strategy sets. In the real business and system design or control problems, however, players' strategy sets may be interactive and each player may have more than one payoff function. This paper investigates the more general situation of multiple payoffs and multiple person games in a normal form. In this paper, each player has several payoff functions, which are dominated by certain convex cones, and the feasible strategy set of each player may be interactive with those of the other players. This new model is applied to a classical example without requiring variational and quasi-variational inequalities, or point-to-set mappings. KEY WORDS: Dominance Cones, Multi-payoff Interactive Games, Variational Inequalities.
Computers & IE, Vol. 37, No. 3, pp. 631-648, 1999. by Theodore B. Trafalis, Tsutomu Mishina, and Bobbie L. Foote School of Industrial Engineering University of Oklahoma 202 W. Boyd, Suite 124 Norman, OK 73019 U.S.A. ABSTRACT: This paper describes a conceptually simple but practical business planning method to cope with uncertain information. The model is constructed by a set of possible scenarios and it is divided into multiple objective functions. Although the resulting model is more complex than traditional stochastic programs, we propose an efficient algorithm in order to offset the difficulties pertaining to the stochastic and multi-objective programming problems. The method provides a wider range of possible solutions. Then the decision-maker selects the least conflicting solution among scenarios by incorporating additional information regarding the problem. An interactive multi-objective programming approach based on a circumscribed ellipsoid interior point algorithm is proposed as an efficient method to solve the problem. KEY WORDS: Interior Point Methods, Ellipsoid Method, Multi-Objective Optimization, Production Planning, Stochastic Optimization, Robust Optimization.
Computers & IE, Vol. 37, No. 3, pp. 649-669, 1999. by Theodore B. Trafalis1 and Rashid M. Alkahtani2 1: School of Industrial Engineering University of Oklahoma 202 W. Boyd, Suite 124 Norman, OK 73019 U.S.A. 2: King Saud University PO Box 2459 Riyadh SAUDI ARABIA 11451 ABSTRACT: This paper proposes the use of an interior point algorithm for Multiobjective Linear Programming (MOLP) problems. At each of step the algorithm the decision-maker furnishes his precise trade-off. From these trade-off a cut is formed in the objective space. This cut induces a cut in the decision space, which defines a half-space of promising points. We compute the analytical center of the restricted feasible region in the decision space and then we calculate the trade-off of the decision-maker at the image of the analytical center in the objective space. Therefore we obtain a trajectory of analytical centers, which converges to the feasible region; it avoids the combinatorial difficulties of visiting extreme points and is less sensitive to problem size.The paper illustrates the method through a numerical example and provides computational experience. KEY WORDS: Multiple Objective Linear Programming, Interactive Methods, Trade-off Cutting Plane, Interior Point Algorithm, Method of Analytic Centers.
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