期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 51, 期 12, 页码 3778-3793出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2013.765077
关键词
flexible job-shop scheduling problem; fuzzy processing time; fuzzy completion time; estimation of distribution algorithm; probability model; design of experiment
资金
- National Key Basic Research and Development Program of China [2013CB329503]
- National Science Foundation of China [61174189, 61025018]
- Doctoral Program Foundation of Institutions of Higher Education of China [20100002110014]
- National Science and Technology Major Project of China [2011ZX02504-008]
Considering the fuzzy nature of the data in real-world scheduling, an effective estimation of distribution algorithm (EDA) is proposed to solve the flexible job-shop scheduling problem with fuzzy processing time. A probability model is presented to describe the probability distribution of the solution space. A mechanism is provided to update the probability model with the elite individuals. By sampling the probability model, new individuals can be generated among the search region with promising solutions. Moreover, a left-shift scheme is employed for improving schedule solution when idle time exists on the machine. In addition, some fuzzy number operations are used to calculate scheduling objective value. The influence of parameter setting is investigated based on the Taguchi method of design of experiment, and a suitable parameter setting is suggested. Numerical testing results and comparisons with some existing algorithms are provided, which demonstrate the effectiveness of the proposed EDA.
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