Appling an improved genetic algorithm for solving the production scheduling problem of steelmaking and continuous casting
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摘要: 煉鋼連鑄制造流程是一個復雜的多階段、多產品生產過程,其生產調度問題可建模為車間調度問題.提出一個改進遺傳算法求解煉鋼連鑄生產調度問題.改進包括三個方面:基于排序的適應度分配、基于排序的工件過濾交叉算子和基于指數關系的變異率曲線.經24個benchmark的比較測試表明,改進遺傳算法比傳統遺傳算法的尋優能力更強.通過16個生產計劃和6個處理工序的煉鋼連鑄生產調度實例計算結果表明,改進遺傳算法是有效的.Abstract: The manufacturing flow of steelmaking and continuous casting is a complex multiple-phase and multiple-product production process.The production scheduling problem in this manufacturing flow can be seen as a job shop scheduling problem.An improved genetic algorithm for solving this problem was proposed and the improved aspects were as follows:rank-based fitness assignment,job filter order-based crossover operator,and mutation rate according to an exponential function relation.Twenty-four benchmarks were comparatively investigated and the result shows that the improved genetic algorithm has a better capacity of seeking optimum than a traditional genetic algorithm.The production scheduling problem of steelmaking and continuous casting with sixteen plans and six procedures was computed using the improved genetic algorithm.It is shown that the algorithm is effective.
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Key words:
- iron and steel plants /
- steelmaking /
- continuous casting /
- job shop scheduling /
- genetic algorithms
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