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A study on comparison of optimization performances between immune algorithm and other heuristic algorithms

机译:免疫算法与其他启发式算法的优化性能比较研究

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摘要

Usefulness of heuristic algorithms as the search method for diverse optimization problems is examined. Immune algorithm (IA), genetic algorithm (GA) and evolution strategy (ES) are used to search the optimal value for some numerical functions. Then those results are compared each other. It is shown that IA is more useful for most of problems. Especially the structure and characteristic of immune algorithm (IA) are inspected in detail. Finally a surface permanent magnet synchronous motor (SPMSM) is designed by using the algorithms.
机译:研究了启发式算法作为各种优化问题的搜索方法的有用性。免疫算法(IA),遗传算法(GA)和进化策略(ES)用于搜索某些数值函数的最优值。然后将这些结果相互比较。结果表明,IA对于大多数问题都更有用。特别是对免疫算法(IA)的结构和特点进行了详细的检查。最后,利用该算法设计了表面永磁同步电动机(SPMSM)。

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