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针对流水车间调度问题提出一种混合遗传NEH算法,以提高求解效率。NEH算法是一种高效的构造性算法具有很强的邻域搜索能力,而遗传算法则能有效地提供全局搜索。据此,新算法首先通过选择、交叉和变异操作,经过迭代获得一个较好解,然后在这个解所在的特定邻域内进行改进的NEH搜索,以获得更好解,经过NEH搜索后求得的最好解作为一个新个体加入下一代种群中,继续进行遗传操作。通过对流水车间调度的最小化最大完成时间问题的仿真实验结果表明,新算法有明显改进。
A hybrid hereditary NEH algorithm is proposed for flowshop scheduling problem to improve the efficiency of solution. The NEH algorithm is an efficient constructor with strong neighborhood search capability, while the genetic algorithm can effectively provide global search. In this way, the new algorithm first obtains a better solution through iteration through selection, crossover and mutation operations, and then makes an improved NEH search in a particular neighborhood where the solution is located to obtain a better solution. After NEH search, The best solution to join as a new individual in the next generation of populations, to continue genetic operation. The result of simulation experiment on minimizing the maximum completion time of the flowshop scheduling shows that the new algorithm has been significantly improved.