A HYBRID GENETIC ALGORITHM FOR MULTISTAGE INTEGRATED LOGISTICS NETWORK OPTIMISATION PROBLEM

Reverse logistics has received growing attention throughout this decade because of the increasing environmental concern, government regulations and economical reasons. The design of reverse logistics network is one of the most important and challenging problems in the field of reverse logistics. This paper proposes a capacitated, multi-echelon, multi-product mixed integer linear programming model for generic integrated logistics network design. The problem includes the decision of the number and location of forward and reverse plants and the distribution network design to satisfy the demands of customers with minimum cost. Because of the complexity of the model, a solution methodology based on the genetic algorithm which hybridizes the heuristic approach with LP is developed. Results obtained by GAMS-CPLEX and proposed solution methodology are compared for different sized test problems.