Optimizing expected holding cost in cellular manufacturing systems with stochastic extensions

Abstract

This research introduces a new application of mathematical modelling for designing cellular manufacturing systems integrated with group scheduling aspects under uncertain conditions. The mixed 0–1 quadratic model is able to optimize group scheduling decisions under lower satisfaction of cell formation decisions. In this way, the required processing time of parts on machines is assumed to be uncertain and also is explained by a discrete set of scenarios. This model tries to optimize the expected scheduling cost in cells plus the subcontracting cost for exceptional operations. In addition, the objectives associated with the cell formation decisions are regarded as constraints by considering the bounded objective technique, one of the multi-objective decision-making techniques. The scheduling problem in a cellular manufacturing framework is treated as group scheduling problem, which assumes that all parts in a part family are processed in the same cell and no intercellular transfer is needed. An efficient modified simulated annealing technique is proposed to solve this complex problem under an optimization rule as a subordinate section. This integrative combination algorithm is compared with global solutions and a heuristic algorithm introduced in the literature. Finally, the performance of the algorithm is verified through some test problems.