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设计了一种嵌套分区算法框架下的局部搜索算法,即基于最优计算量分配技术的序遗传算法,该算法采用序优化思想保证在有限计算量条件下得到局部最优解,并用遗传算法的进化搜索能力和学习能力对解空间进行搜索。将设计的局部搜索算法与嵌套分区算法相结合提出一种新的混合优化算法,用该混合优化算法求解几个标准的随机车间调度问题,数字仿真的结果表明该混合算法的优化性能好于遗传算法及基于最优计算量分配技术的序优化方法。
A local search algorithm under the framework of nested partitioning algorithm is designed, that is, an ordered genetic algorithm based on optimal computational allocation technique. The algorithm adopts order optimization idea to ensure that the local optimal solution is obtained under the condition of limited computational load. Genetic algorithm The evolution of search capabilities and learning ability to search the solution space. A new hybrid optimization algorithm is proposed by combining the local search algorithm with nested partitioning algorithm. The hybrid optimization algorithm is used to solve several standard stochastic shop scheduling problems. The numerical simulation results show that the hybrid algorithm has better performance Genetic Algorithms and Ordinal Optimization Method Based on Optimal Calculation Quantity Allocation.