An efficient memetic algorithm for the multi-stage supply chain network problem

A supply chain is dynamic and involves the constant flow of information, production, services, and funds from suppliers to customers between different stages. In this paper, a memetic algorithm (MA, a hybrid genetic algorithm) is developed to find the strategy that can give the lowest cost of the physical distribution flow. The proposed MA is combined with the genetic algorithm (GA), a multi-greedy heuristic method (GH), three local search methods (LSMs): the pairwise exchange procedure (XP), the insert procedure (IP), and the remove procedure (RP), the Fibonacci number procedure, and the linear programming technique (LP) to improve the tradition genetic algorithm (GA). Preliminary computational experiments demonstrate the efficiency and performance of the proposed MA.