Genetic algorithm-based heuristic for capacitated lotsizing problem in flow shops with sequence-dependent setups

Research highlights� Presenting a more efficient heuristic approach for the problem of lotsizing in capacitated flow shops with sequence-dependent setups is the main focus of our research. � Our proposed heuristic combines genetic algorithm with rolling horizon approach. The full factorial design has been used to calibrate the heuristic. � In order to evaluate the effectiveness of the proposed heuristic, some numerical experiments are generated and corresponding results are compared with those of formerly developed heuristics. � The comparative results indicate the superiority of proposed heuristic specially in solving the large-sized problem instances. This paper proposes a genetic algorithm-based heuristic for the capacitated lotsizing problem in flow shops with sequence-dependent setups. The proposed heuristic combines genetic algorithm with rolling horizon approach. To evaluate the effectiveness of the proposed heuristic, some numerical experiments are conducted and corresponding results are compared with those of previously developed heuristics by authors. The comparative results indicate the superiority of genetic algorithm-based heuristic specially in solving the large-sized problem instances.

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