3机Flow-shop调度问题研究
STUDY OF THREE-MACHINE FLOW-SHOP SCHEDULING PROBLEM
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摘要: 提出了一种遗传分枝定界算法求解3机Flow-shop调度问题,该算法类似于常用的遗传局部算法和遗传动态规划算法.用随机方法生成测试例子,通过与著名的Taillard的禁忌搜索算法和Reeves的遗传算法进行比较,实验结果证实了遗传分枝定界算法的有效性.Abstract: A genetic branch and bound algorithm is proposed to solve the 3 machine flow-shop permutation problem, which is similar to often used the genetic local algorithm and the genetic dynamic programming algorithm. Based on the test examples that are produced with random methods and the performance Comparison with the famous Taillard'tuba search algorithm and Reeves'genetic algorithm, the experimental results show the effectiveness of the genetic branch and bound algorithm.