Supply and Production/Distribution Planning in Supply Chain with Genetic Algorithm

Abstract

The present study, using genetic algorithm, tries to improve material flow management in supply chain. Consequently, in this paper, an integrated supply-production and distribution planning (SPDP) is considered despite the fact that in most of the Iranian industrial firms, SPDP is done independently. The effective use of integrated SPDP not only enhances the performance rather decreases inventory cost, holding cost, shortage cost and overall supply chain costs. A quantitative mathematical model is used to the problem articulation, and then it is solved by applying heuristic genetic algorithm (GA) method. The proposed model with genetic algorithm could provide the best satisfactory result with the minimum cost. The reliability test was carried by comparing the model results with that of the amount of variables.

Research and Application of Supply Chain Distribution Optimization Model based on Improved Genetic Algorithm

“…It can be found out that the initial population includes a lot of tour paths, while this result in practical distribution is not reasonable and not realistic in distribution activities. For example, in K initial 1 = [9,3,9,11,7,17,14,8,9,3,3,1,2,4,1,13,1,17,11,16], path [9 3 9] is a tour path, which is not allowed in operation. Design pretreatment operator and deal with the repeated path and tour path in the path.…”