A ROBUST CREDIBILITY-BASED FUZZY PROGRAMMING FOR PRODUCTION-ROUTING PROBLEMS WITH CELL FORMATION - Jeshvaghani, Mina Dehghani; Amiri, Maghsoud; Olfat, Laya; Vahdat, Vahab; Khalili-Damghani, Kaveh (International Journal of Industrial Engineering: Theory, Applications and Practice, 2022)
Production-routing problem (PRP) integrates different decisions along the supply chain simultaneously. Studies on PRP only determine the amount and time of production in a linear and continuous production system. While for the supply chain with scattered and different customers, it is necessary to have a flexible production system such as <a href="https://www.google.com/search?rlz=1C1AVNA_enUA828US828&sxsrf=APq-WBvcZVtTPkDaGivgDFMXqYzfeObkcg:1647278955509&q=cellular+manufacturing&spell=1&sa=X&ved=2ahUKEwjT_vOnkMb2AhWVQvEDHRtzBbwQkeECKAB6BAgCEDI">a cellular manufacturing system (CMS). The proposed model incorporates the cell formation problem (CFP) into a PRP. This designing problem in CMS determines the allocation of machines and products to cells and reduces the cost of intercellular movements. We apply a Robust credibility-based fuzzy programming (RCFP) approach versus the possibilistic chance-constrained programming (PCCP) for demand uncertainty. We optimize the model by Teaching-Learning-based Optimization (TLBO) and simulated annealing (SA) algorithms. The convergence in results shows the effectiveness of both algorithms, especially the TLBO algorithm. Furthermore, RCFP leads to a more robust solution with the intelligent choice of the confidence level for satisfying chance constraints and less sensitivity to the changes in non-deterministic parameters.