Multi-criteria genetic optimization for distribution network problems

This paper develops a multi-criterion genetic optimization for solving distribution network problems in supply chain management. Distribution problems deal with distribution from a number of sources to a number of destinations, in which various decision factors are closely related and influence each other. Genetic algorithms have been widely adopted as the optimization tool in solving these problems. This paper combines analytic hierarchy processes with genetic algorithms to capture the capability of multi-criterion decision-making. The proposed algorithm allows decision-makers to give weightings for criteria using a pairwise comparison approach. The numerical results obtained from the new approach are compared with the results obtained from linear programming. The result shows that the proposed algorithm is reliable and robust. In addition, it provides more control for decision-makers on the determination of the optimization solutions, and gains more information for a better insight into the distribution network. This revised version was published online in October 2004 with a correction to the issue number.