Dynamic virtual cellular reconfiguration for capacity planning of market-oriented production systems

Market-oriented production systems generally have the characteristics of multi-product and small-batch production. Dynamic virtual cellular manufacturing create cells periodically in a planning horizon to respond changing demands flexibly quickly, thus are suitable for problems market-oriented systems. In current research, we propose dynamic cell reconfiguration framework under environment with unstable multiple cycles. this framework, formulate two-phase formation (DVCF) model. first phase, proposed model aims maximize processing similarity balance workload system. second consider objective stability based on phase To address model, design hybrid metaheuristic named Lévy-NSGA-?, perform various computational experiments examine performance algorithm. Results indicate that Lévy-NSGA-? algorithm outperforms multi-objective cuckoo search (MOCS) NSGA-? solution quality optimal size.