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An Approximate Algorithm Combining P Systems and Active Evolutionary Algorithms for Traveling Salesman Problems

机译:结合P系统和主动进化算法求解旅行商问题的近似算法。

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An approximate algorithm combining P systems and active evolutionary algorithms (AEAPS) to solve traveling salesman problems (TSPs) is proposed in this paper. The novel algorithm uses the same membrane structure, subalgorithms and transporting mechanisms as Nishida's algorithm, but adopts two classes of active evolution operators and a good initial solution generating method. Computer experiments show that the AEAPS produces better solutions than Nishida's shrink membrane algorithm and similar solutions with an approximate optimization algorithm integrating P systems and ant colony optimization techniques (ACOPS) in solving TSPs. But the necessary number of iterations using AEAPS is less than both of them.
机译:提出了一种结合P系统和主动进化算法(AEAPS)来解决旅行商问题(TSP)的近似算法。新算法使用与Nishida算法相同的膜结构,子算法和传输机制,但是采用了两类主动进化算子和良好的初始解生成方法。计算机实验表明,AEAPS可以比Nishida的收缩膜算法和类似的解决方案提供更好的解决方案,该解决方案通过将P系统和蚁群优化技术(ACOPS)集成在一起的近似优化算法来求解TSP。但是,使用AEAPS进行迭代的必要次数少于两者。

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