A constraint programming approach for production scheduling of multi-period virtual cellular manufacturing systems

Virtual cellular manufacturing systems (VCMSs) have drawn significant attention in recent years because traditional cellular manufacturing systems (CMSs) are inadequate in a highly dynamic manufacturing environment. In this paper, a new mathematical model is presented to formulate the production schedules of virtual cellular manufacturing systems in a multi-period planning horizon, where the product mix and demand are different but deterministic in each period. The model takes backlog of jobs into consideration and aims to minimize the total manufacturing cost over the entire planning horizon. A constraint programming (CP) approach is developed to solve this difficult scheduling problem effectively by depicting it as an associate constraint network where nodes and arcs represent the operations of the jobs and their associations respectively. An innovative backmarking propagation technique is proposed to search for a set of feasible production sequences. Some effective heuristics are also developed to facilitate the formation of complete schedule solutions. Results of extensive experiments on a set of randomly generated test problems show that the constraint programming approach outperforms the genetic algorithm in terms of both solution quality and computational time.