Improvement of Evolutionary Ability of Heat Exchange Network Structure with Periodic Advantage Structure Extraction and Search Path Enhancement

doi:10.19596/j.cnki.1001-246x.8147

Abstract

Abstract: To solve the problem that the forced evolutionary random walk algorithm (RWCE) falls into local optimization and reduces search ability in the later stage of optimization,a strategy of combining periodic dominance structure extraction with search path enhancement is proposed. Firstly,population of the system is preliminarily optimized,and the dominant individuals are extracted in certain period.Then these dominant individuals are replicated by multiple paths to other individuals. Finally,according to the search mechanism,they are spread all over the whole solution domain. It shows that the multi-path search strategy centered on dominant individuals improves accuracy of local optimization,increases diversity of population,enhances global search ability,and improves efficiency and quality of optimization.

Key words: random walk algorithm with compulsive evolution, population diversity, global search

CLC Number:

TK172

JIN Yan, CUI Guomin, CAO Mei, SHEN Hao, CHEN Zihe. Improvement of Evolutionary Ability of Heat Exchange Network Structure with Periodic Advantage Structure Extraction and Search Path Enhancement[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 2020, 37(6): 725-733.

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