A Genetic Algorithm Based Optimization Approach For Production-Distribution Problem
Production-Distribution planning (PDP) is a tactical decision problem for Supply Chain Systems (SCS). It aims to optimize supply, production and distribution systems of a chain. In this study, a PDP for a multi-echelon SCS which has suppliers, plants, warehouses, retailers has been considered. A, 0 – 1 mix integer programming model has been developed for the PDP. The mathematical model can be solved global optimal for small size problems. However, it is not possible to solve PDP when the numbers of suppliers, plants, products, warehouses, retailers and transportation paths increase. In this study, a Genetic Algorithm based optimization (GA) has been developed to solve large size PDP. The proposed GA algorithm has been tested for small size PDPs. The results showed that the proposed GA algorithm is successful in finding solutions within of 4 % of known optimal solutions. Then, it has been tested on a randomly generated large size PDP which cannot be solved by optimization software.
Keywords: Production Distribution, Supply Chain System, Genetic Algorithm.