期刊
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
卷 51, 期 5-8, 页码 757-767出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00170-010-2642-2
关键词
Flexible job-shop scheduling; Multi-objective genetic algorithm; Pareto-optimality; Immune and entropy principle
资金
- National High-Tech Research and Development Program of China (863 Program) [2007AA04Z107]
- National Natural Science Foundation of China [60973086, 50825503]
- program for New Century Excellent Talents in University [NCET-08-0232]
Flexible job-shop scheduling problem (FJSP) is an extended traditional job-shop scheduling problem, which more approximates to practical scheduling problems. This paper presents a multi-objective genetic algorithm (MOGA) based on immune and entropy principle to solve the multi-objective FJSP. In this improved MOGA, the fitness scheme based on Pareto-optimality is applied, and the immune and entropy principle is used to keep the diversity of individuals and overcome the problem of premature convergence. Efficient crossover and mutation operators are proposed to adapt to the special chromosome structure. The proposed algorithm is evaluated on some representative instances, and the comparison with other approaches in the latest papers validates the effectiveness of the proposed algorithm.
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