A multi-criterion genetic algorithm for order distribution in a demand driven supply chain

Abstract

This paper develops a multi-criterion genetic optimization procedure, specifically designed for solving optimization problems in supply chain management. The proposed algorithm is discussed with an order distribution problem in a demand driven supply chain network. It combines the analytic hierarchy process (AHP) with genetic algorithms. AHP is utilized to evaluate the fitness values of chromosomes. The proposed algorithm allows decision-makers to give weighting for criteria using a pair-wise comparison approach. The numerical results obtained from the proposed algorithm are compared with the one obtained from the multi-objective mixed integer programming approach. The comparison shows that the proposed algorithm is reliable and robust. In addition, it provides more control and information for the decision-makers to gain a better insight of the supply chain network.