Hybrid firefly-simulated annealing algorithm for the flow shop problem with learning effects and flexible maintenance activities

作者：Nouri Behdin Vahedi; Fattahi Parviz^*; Ramezanian Reza

来源：International Journal of Production Research, 2013, 51(12): 3501-3515.

DOI：10.1080/00207543.2012.750771

• scheduling
• non-permutation flow shop
• learning effect
• availability constraint
• heuristic method
• hybrid firefly-simulated annealing algorithm
• Taguchi method

Job scheduling and maintenance activities scheduling are two important issues in production management, which are often addressed separately. In this paper, the non-permutation flow shop scheduling problem with learning effects and flexible maintenance activities is studied. Each machine has a number of preventive maintenance activities that should be finished within specific time intervals. The aim is to simultaneously determine the sequence of jobs and the finish time of maintenance activities for minimising the sum of tardiness costs and maintenance costs. A mixed integer linear programming model is proposed to formulate the problem. Owing to the high complexity of the problem, an improvement heuristic method and a hybrid meta-heuristic algorithm based on the simulated annealing algorithm and firefly algorithm is presented to find nearly optimal solutions for medium and large problems. To obtain better and more robust solutions, the Taguchi method is used in order to calibrate the hybrid algorithm parameters. Finally, the computational results are provided for evaluating the performance and effectiveness of the proposed solution approaches.

• 出版日期2013-6-1