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Hybrid fireworks algorithm with differential evolution operator

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成果类型:
期刊论文
作者:
Jinglei Guo;Wei Liu;Ming Liu(刘明);Shijue Zheng
通讯作者:
Guo, J.
作者机构:
[Ming Liu; Jinglei Guo; Wei Liu; Shijue Zheng] School of Computer Science, Central China Normal University, Wuhan 430079, China
通讯机构:
School of Computer Science, Central China Normal University, Wuhan, China
语种:
英文
关键词:
Benchmarking;Explosions;Explosives;Ion exchange;Natural resources exploration;Optimization;Swarm intelligence;DE operator;Exploitation;Fireworks algorithms;Hybrid;Intelligent information;Optimisation problems;Evolutionary algorithms
期刊:
International Journal of Intelligent Information and Database Systems
ISSN:
1751-5858
年:
2019
卷:
12
期:
1-2
页码:
47-64
基金类别:
This work is supported by National Key Technology Research and Development Program of the Ministry of Science and Technology of China. (No. 2015BAK33B03) and the self-determined research funds of CCNU from the colleges basic research and operation of MOE (No. CCNU18QN018).
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
As a population-based intelligence algorithm, fireworks algorithm simulates the fireworks' explosion process to solve optimisation problem. A comprehensive study on enhanced fireworks algorithm (EFWA) reveals that the explosion operator generates too much sparks for the best firework limits the exploration ability. A hybrid version of EFWA (HFWA_DE) is proposed by adding the differential evolution (DE) operator. In HFWA_DE, the population is divided into two subpopulations, then each subpopulation evolves with FWA operator and DE operator separately and exchanges the elitist individual. Experi...

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