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基于改進遺傳算法的車削加工中心工步排序與優(yōu)化
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Worksteps Sequencing and Optimization of Mill/turn Machining Center Based on Improved Genetic Algorithm
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    摘要:

    多主軸多動力刀架車削加工中心工步排序問題是同時涉及資源調(diào)度和工步排序的復(fù)雜問題。提出一種改進遺傳算法以解決結(jié)合工藝資源調(diào)度的車削加工中心工步排序問題。通過建立0-1混合整數(shù)規(guī)劃模型,為算法提供目標(biāo)函數(shù)及約束,并根據(jù)此模型中多參數(shù)多約束的特點,設(shè)計了一種基于結(jié)構(gòu)體的編碼方法。為改善算法性能,根據(jù)相鄰基因間的相似程度,構(gòu)造了多概率交叉算子與多概率變異算子,從而提高由相鄰基因組成優(yōu)秀基因段遺傳至下一代的概率。實例表明該遺傳算法具有可行性與有效性,并且較傳統(tǒng)遺傳算法在解決該類問題方面具有更好的收斂性。

    Abstract:

    Mill/turn machining center can perform several operations simultaneously with multiple spindles and power turrets, which means worksteps sequencing should be integrated with scheduling. According to the characteristics of mill/turn machining center, an improved genetic algorithm to optimize worksteps sequence was proposed. A 0-1 mixed integer programming model was set up to support the algorithm with object function and constraints. In order to present so many parameters of the 0-1 mixed integer programming model, coding strategy was developed based on data structure instead of integer or symbol. According to the similarity of genes, two novel genetic operators named multi-probability crossover operator and multi-probability mutation operator were also introduced. Consequently, these genetic operators insure that chromosomes consisted of genes with more similarity could transmit their characteristics to next generation with higher probability. The effectiveness of the proposed algorithm was verified by a real case using dual spindles and twin power turrets mill/turn machining center. The results also indicated that the improved genetic algorithm gained a better performance than the conventional genetic algorithm.

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蘇於梁,褚學(xué)寧,孫習(xí)武,湯岑書.基于改進遺傳算法的車削加工中心工步排序與優(yōu)化[J].農(nóng)業(yè)機械學(xué)報,2010,41(8):216-222.Worksteps Sequencing and Optimization of Mill/turn Machining Center Based on Improved Genetic Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(8):216-222.

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