首页> 外文会议>Computer Supported Cooperative Work in Design, 2009. CSCWD 2009 >Similarity based ant-colony algorithm for permutation flowshop scheduling problems with total flowtime minimization
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Similarity based ant-colony algorithm for permutation flowshop scheduling problems with total flowtime minimization

机译:总流时最小化的置换Flowshop调度问题的基于相似度的蚁群算法

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In the paper, a similarity based ant-colony algorithm (SACO) is proposed for the permutation flowshop scheduling problems with total flowtime minimization, which is known as NP-hard. By applying the space mapping method which is testified to be reasonable, it is proved theoretically that the deposit factor rho has hardly impact on the ACO evolutionary availability, and rho = 0.5 is reasonable for the ACO. Similarity is defined to discover the promising sequence for solution improvement. A new solution construction method is proposed, which is stated to be better than that of another very effective ant-colony algorithm. Experimental results show that SACO outperforms the other compared seven algorithms, including three rather recent effective algorithms and four famous ant-colony algorithms. The similarity indeed helps the SACO to find the promising sequence for solution improvement, which makes the SACO be effective.
机译:针对总流时最小化的置换流水车间调度问题,提出了一种基于相似度的蚁群算法(SACO),称为NP-hard。通过应用经证明是合理的空间映射方法,从理论上证明了沉积因子rho对ACO的演化可用性几乎没有影响,而rho = 0.5对于ACO是合理的。定义相似性以发现解决方案改进的有希望的顺序。提出了一种新的解决方案构造方法,该方法被认为比另一种非常有效的蚁群算法更好。实验结果表明,SACO优于其他七个比较算法,包括三个较新的有效算法和四个著名的蚁群算法。相似性的确有助于SACO找到有希望的解决方案改进顺序,从而使SACO变得有效。

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