Parameter combination framework for the differential evolution algorithm
type: Item
instance of: scholarly article
title: Parameter combination framework for the differential evolution algorithm
zbMATH Open document ID: 1461.90200
author: Jinghua Zhang
author: Ze Dong
published in: Algorithms
publication date: 2019-07-08T00:00:00Z
review text: Summary: The differential evolution (DE) algorithm is a popular and efficient evolutionary algorithm that can be used for single objective real-parameter optimization. Its performance is greatly affected by its parameters. Generally, parameter control strategies involve determining the most suitable value for the current state; there is only a little research on parameter combination and parameter distribution which is also useful for improving algorithm performance. This paper proposes an idea to use parameter region division and parameter strategy combination to flexibly adjust the parameter distribution. Based on the idea, a group-based two-level parameter combination framework is designed to support various modes of parameter combination, and enrich the parameter distribution characteristics. Under this framework, two customized parameter combination strategies are given for a single-operation DE algorithm and a multi-operation DE algorithm. The experiments verify the effectiveness of the two strategies and it also illustrates the meaning of the framework.
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 90C26
zbMATH DE Number: 7077446
zbMATH Keywords: differential evolution (DE)
zbMATH Keywords: global optimization
zbMATH Keywords: parameter control strategy
zbMATH Keywords: parameter strategy combination
zbMATH Keywords: parameter region combination
describes a project that uses: CEC 13
describes a project that uses: JADE
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a12040071
OpenAlex ID: W2925966168
cites work: Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
cites work: Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations
cites work: Infeasibility and structural bias in differential evolution
cites work: Q5699569
cites work: A fuzzy adaptive differential evolution algorithm
cites work: Harmony search based parameter ensemble adaptation for differential evolution
DOI: 10.3390/A12040071
description: scientific article; zbMATH DE number 7077446