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Automatic rule combination approach for single-stage process scheduling problems
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DOI：10.1002/aic.11236.png)
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摘要
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Meta-heuristic methods show better performance in solving large-size sequential process scheduling problems than mixed-integer linear programming. Heuristic rules are often used in meta-heuristic methods and play a very important role in reducing search space of the scheduling problems. In our previous work (He and Hui, Ind Eng Chem Res. 2006; 45: 4679-4692), approaches of how to automatically select rules from a set of heuristic rules have been proposed. This work proposes a novel approach of how to construct a comprehensive, but not very large set of rules according to the analysis of impact factors. Working with the new rule set, the original approaches are improved, in which a full rule sequence is used for schedule synthesis. A new automatic rule combination approach is proposed, in which a partial rule sequence is intentionally formed and used for schedule synthesis. The adoption of the partial rule sequences saves computational sources and increases the search ability of the algorithms. The automatic rule combination approach almost has the same search ability as the long time tabu search to find the near-optimal solutions to the large-size problems, but with much higher convergence speed. (c) 2007 American Institute of Chemical Engineers.
Keyword:
sequential process scheduling
impact factors
heuristic rules
genetic algorithm
rule evolution
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IF:
4
论文数:
1.1W
被引数:
2.9W
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