Generating Alternatives for Siting Using Genetic Algorithms and Multiple Criteria Decision Techniques

Abstract

It is believed that a fundamental step in the structuring of a siting problem is generating alternati-ves. This task should occur at the beginning of a process for facility location, giving a preliminary insight into the feasibility of the project in the area of concern by identifying a manageable number of feasible alternatives for careful review and consideration. The purpose of this paper is to present a methodology aimed at generating alternatives for siting of facilities taking into account a number of criteria. These criteria comprise environmental, economical and the action's inherent technical aspects. The search is carried out by applying genetic algorithms (GA's) which are natural phenomena based algorithms for optimization and random search procedures. According to the GA's terminology, a fitness function measures the worth of each candidate alternative codified into a chromosome. It was thought that the merging of aspects of multiple criteria theory and genetic algorithms is essential for the problem of generating alternatives in location problems. The aim of this integration is the improvement of the theoretical principles upon which the fitness function is based, leading to the construction of a robust set of alternatives. The paper describes the integration of both multiple criteria theory and GA's and discusses the results