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A parallel harmony search algorithm with dynamic harmony-memory size

机译:动态和声大小的并行和声搜索算法

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摘要

Inspired by the concept of swarm intelligence,a parallel harmony search algorithm with dynamic harmony-memory size (PDHS) is presented to solve unconstrained problems.The PDHS algorithm has two significant operations: Harmony Memory (HM) grouping and Harmony Memory Size (HMS) updating.In the former operation,the harmony memory is divided into several groups named sub-HMs which help decreasing the optimization time because of their parallel searching.In the latter operation,the HMS value is dynamically changed according to the given rules during the iteration,which helps keeping the diversity of harmonies and supporting greater exploration in search space.Various benchmark optimization problems are tested to demonstrate the effectiveness of the proposed algorithm.The simulation results reveal that the proposed PDHS algorithm can get better solutions and is more efficient than the original HS algorithm in most cases.
机译:受到群体智能概念的启发,提出了一种具有动态和谐内存大小(PDHS)的并行和谐搜索算法来解决无约束的问题。PDHS算法具有两个重要的运算:和声记忆(HM)分组和和声记忆大小(HMS)在前一种操作中,和声存储器被分为几组,称为子HM,这有助于减少它们的并行搜索,从而缩短了优化时间。在后一种操作中,HMS值在迭代过程中根据给定的规则动态变化。对各种基准优化问题进行了测试,证明了所提算法的有效性。仿真结果表明,所提出的PDHS算法可以得到更好的解决方案,并且效率更高。大多数情况下使用原始HS算法。

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