Optimization of logistic processes in supply-chains using meta-heuristics

Abstract

This paper addresses the optimization of logistic processes in supply-chains using meta-heuristics: genetic algorithms and ant colony optimization. The dynamic assignment of components to orders and choosing the solution that is able to deliver more orders at the correct date, is a scheduling problem that classical scheduling methods can not cope with. However, the implementation of meta-heuristics is done only after a positive assessment of the performance's expectation provided by the fitness-distance correlation analysis. Both meta-heuristics are then applied to a simulation example that describes a general logistic process. The performance is similar for both methods, but the ant colony optimization method provides more information at the expenses of computational costs. © Springer-Verlag Berlin Heidelberg 2003.