An ERNSGA‐III algorithm for the production and distribution planning problem in the multiagent supply chain. (20th March 2019) - Gharaei, Ali; Jolai, Fariborz
Abstract: Nowadays, new issues have been emerged in industry by increasing the supply chain boundaries, especially when some supply chain members seek their own interests. In the literature, this case is referred to as a multiagent problem in which each agent has his/her own set of jobs and objectives. Here, an integrated production scheduling and distribution problem in a multisite supply chain is investigated from the three‐agent perspective of the manufacturer, distributor, and customer. Due to the complexity of the problem, a novel evolutionary‐based reference point determination of the third version of the non‐dominated sorting genetic algorithm (ERNSGA‐III) is proposed. In this algorithm, some modifications to the classic version of NSGA‐III have been made and a novel reference point determination method based on Bees algorithm is used in the selection operation. Some statistical tests are performed to compare the proposed algorithm with three other algorithms in the literature. The results show that the proposed algorithm is more effective than other algorithms.