一种结合并行处理机制的差分进化方法

Dong-Hyun Lim, Hoang N. Luong, C. Ahn
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引用次数: 2

摘要

在本文中,我们将并行机制引入差分演化(DE)。差分进化算法存在个体聚集在一个点上,无法逃离局部最优的盆地的问题。我们提出并行处理来解决这个问题。并行处理帮助DE保持多个最佳个体(吸引子)。不同的吸引子帮助DE向不同的方向扩展其搜索。我们将我们的方法命名为以并行方式处理的差分进化算法(P-DE)。在各种测试问题中,将P-DE与原始DE进行比较,显示出其优越的性能。
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A Novel Differential Evolution Incorporated with Parallel Processing Mechanism
In this paper, we introduce the parallel mechanism to the Differential Evolution (DE). Differential Evolution algorithm suffers from the problem that individuals gather in a single point and cannot escape the basin of a local optimum. We propose the parallel processing as a solution to this problem. Parallel processing helps DE maintain more than one best individual (attractor). Different attractors help DE expand its search towards various directions. We name our approach a differential evolution algorithm processed in the parallel fashion (P-DE). P-DE, when compared with the original DE in various test problems, exhibits its superior performance.
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