A Genetic Algorithm for Multicriteria Inventory Classification

One of application areas of the genetic algorithms is parameter optimization. This paper addresses the problem of optimizing a set of parameters that represent the weights of criteria, where the sum of all weights is 1. A chromosome represents the values of the weights, possibly along with some cut-oo points. A new cross-over operation, called continuous uniform crossover, is proposed, such that it produces valid chromosomes given that the parent chromosomes are valid. The new crossover technique is applied to the problem of multi-criteria inventory classiication. The results are compared with the classical inventory classiication technique using Analytical Hierarchy Process.