南京航空航天大学学报（英文版）2006，Vol.23Issue(2)：144-148,5.
基于IOCDGA的模糊目标柔性作业车间调度优化
FLEXIBLE JOB-SHOP SCHEDULING WITH FUZZY GOAL THROUGH IOCDGA
摘要
Abstract
The fuzzy goal flexible job-shop scheduling problem (FGFJSP) is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-object problem, such as the fuzzy cost, the fuzzy due-date, and the fuzzy makespan, etc, can be solved by FGFJSP. To optimize FGFJSP, an individual optimization and colony diversity genetic algorithm (IOCDGA) is presented to accelerate the convergence speed and to avoid the earliness. In IOCDGA, the colony average distance and the colony entropy are defined after the definition of the encoding model. The colony diversity is expressed by the colony average distance and the colony entropy. The crossover probability and the mutation probability are controlled by the colony diversity. The evolution emphasizes that sigle individual or afew individuals evolve into the best in IOCDGA, but not the all in classical GA. Computational results show that the algorithm is applicable and the number of iterations is less.关键词
遗传算法/柔性/作业车间调度/模糊目标Key words
genetic algorithm/flexible/job-shop scheduling/fuzzy goal分类
信息技术与安全科学引用本文复制引用
袁坤,朱剑英,孙志峻..基于IOCDGA的模糊目标柔性作业车间调度优化[J].南京航空航天大学学报（英文版）,2006,23(2):144-148,5.基金项目
Supported by the National Natural Science Foundation of China(59990470).国家自然科学基金(59990470)资助项目. （59990470）
