Modeling and evolutionary optimization on multilevel production scheduling: a case study

  • Authors:
  • Ruifeng Shi;Chunxia Shangguan;Hong Zhou

  • Affiliations:
  • School of Control & Computer Engineering, North China Electric Power University, Beijing, China;College of Engineering Science & Technology, Shanghai Ocean University, Shanghai, China;School of Economics & Management, Beihang University, Beijing, China

  • Venue:
  • Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
  • Year:
  • 2010

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Abstract

Multilevel production scheduling problem is a typical combinatorial optimization problem in a manufacturing system, which is traditionally modeled as several hierarchical sublevel problems and optimized at each level, respectively. An integrated model, which can cope with the whole multilevel scheduling information simultaneously, is proposed in this paper, and a specific evolutionary algorithm is designed to solve the integrated model with a twin-screw coding strategy. In order to evaluate the performance of the new algorithm, a real 3-level production scheduling problem is employed for case study, and two typical metaheuristic algorithms, a genetic algorithm (GA) and a simulated annealing (SA), are also employed for comparison study. Experimental simulation results show that our proposed modeling and optimization method has outperformed the other ones.