A new genetic algorithm for flexible job-shop scheduling problems

作者：Driss Imen^*; Mouss Kinza Nadia; Laggoun Assia

来源：Journal of Mechanical Science and Technology, 2015, 29(3): 1273-1281.

DOI：10.1007/s12206-015-0242-7

• FJSP
• Scheduling
• Genetic algorithm
• Chromosome representation

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

• 出版日期2015-3