An evolutionary approach to support decision making with linear decision models

In this paper we consider decision problems that can be described as linear decision models. These models have been traditionally solved using linear programming, fuzzy linear programming, multiple-objective linear programming or ‘what-if’ analysis. Using these approaches, one encounters a number of difficulties. We propose an ‘evolutionary approach’ to overcome these difficulties. In the proposed approach the decision maker does not have to precisely specify the model (i.e. the objective functions, the RHS values, etc.) at the beginning of the solution procedure. In fact, the model evolves as the solution procedure proceeds.     

A parameter analysis method for the weight‐set to satisfy preference orders of alternatives in additive multi‐criteria value models

In the context of the additive multi‐criteria value model, this paper investigates how the set of criteria weights (weight‐set hereafter) can be determined according to the preference orders of alternatives given by the decision maker. A construction method is proposed for the weight‐set for different intervals of β, where β is a differential amount of value between the preference information on two alternatives. The results of this paper are important for sensitivity analysis in multi‐criteria decision making (MCDM) problems and multi‐criteria group decision analysis. Copyright © 2000 John Wiley & Sons, Ltd.     

An application of visual interactive goal programming: a case in vendor selection decisions

This article presents the vendor selection problem of the hydraulic pump division of a US original equipment manufacturing company. The division wants to identify appropriate vendors and allocate purchase orders among them while minimizing product acquisition costs and maximizing total product quality and delivery reliability. Visual interactive goal programming is used as a multi‐criteria decision analysis tool. Interaction with decision makers during the model building and solution process, and implications are discussed. Copyright © 1999 John Wiley & Sons, Ltd.     

Relative importance of criteria: a quantitative approach

A mathematical definition for the assertion ‘a group of criteria A is more important than a group of criteria B’ is introduced. It is shown how quantitative information on relative importance of criteria allows us to obtain a more precise upper estimate for a set of all non-dominated solutions than the well-known Pareto set. © 1997 John Wiley & Sons, Ltd.