A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem

作者：Rohaninejad Mohamad; Kheirkhah Amirsaman; Fattahi Parviz^*; Vahedi Nouri Behdin

来源：International Journal of Advanced Manufacturing Technology, 2015, 77(1-4): 51-66.

DOI：10.1007/s00170-014-6415-1

• Scheduling
• Flexible job shop
• Multi-objective genetic algorithm
• ELECTRE method
• Pareto optimal front

In this paper, a multi-objective flexible job shop scheduling problem with machines capacity constraints is studied. Minimizing the makespan and overtime costs of machines are considered as two objectives for evaluating solutions. First, a new nonlinear integer programming model is presented to formulate the problem. Inasmuch as this problem is well-known as a NP-hard problem, a hybrid metaheuristic algorithm (CFJSP II) is developed to overcome its complexity. Regarding to the solution space of the problem, for assigning and sequencing operations, a multi-objective genetic algorithm based on the ELECTRE method is presented. Also, a powerful heuristic approach to tradeoff the objective functions is developed. Finally, the proposed algorithm is compared with some well-known multi-objective algorithms such as NSGAII, SPEA2, and VEGA. Regarding to the computational results, it is clear that the proposed algorithm has a better performance especially in the closeness of the solutions to the Pareto optimal front.

• 出版日期2015-3