A novel collaborative optimization algorithm in solving complex optimization problems

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Deng, Wu;Zhao, Huimin*;Zou, Li;Li, Guangyu;Yang, Xinhua;...

通讯作者：

Zhao, Huimin

作者机构：

[Zhao, Huimin; Zou, Li; Deng, Wu; Li, Guangyu; Yang, Xinhua] Dalian Jiaotong Univ, Software Inst, Dalian 116028, Peoples R China.

[Zhao, Huimin; Deng, Wu] Guangxi Univ Nationalities, Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China.

[Zou, Li; Deng, Wu; Li, Guangyu] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China.

[Zou, Li; Deng, Wu] Southwest Jiaotong Univ, Tract Power State Key Lab, Chengdu 610031, Peoples R China.

[Zhao, Huimin; Deng, Wu] Guangxi Univ Nationalities, Key Lab Guangxi High Sch Complex Syst & Computat, Nanning 530006, Peoples R China.

通讯机构：

[Zhao, Huimin] D

[Zhao, Huimin] G

Dalian Jiaotong Univ, Software Inst, Dalian 116028, Peoples R China.

Guangxi Univ Nationalities, Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China.

Guangxi Univ Nationalities, Key Lab Guangxi High Sch Complex Syst & Computat, Nanning 530006, Peoples R China.

语种：

英文

关键词：

Genetic algorithm;Ant colony optimization algorithm;Chaotic optimization method;Multi-strategy;Collaborative optimization;Complex optimization problem

期刊：

Soft Computing

ISSN：

1432-7643

年：

2017

卷：

期：

页码：

4387-4398

DOI：

10.1007/s00500-016-2071-8

基金类别：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [U1433124, 51475065]; Open Project Program of State Key Laboratory of Mechanical Transmissions (Chongqing University) [SKLMT-KFKT-201416, SKLMT-KFKT-201513]; Natural Science Foundation of Liaoning ProvinceNatural Science Foundation of Liaoning Province [2015020013]; Open Fund of Key Laboratory of Guangxi High Schools for Complex System & Computational Intelligence [15CI06Y]; Open Project Program of Guangxi Key laboratory of hybrid computation and IC design analysis [HCIC201507, HCIC201402]; Open Project Program of the Traction Power State Key Laboratory of Southwest Jiaotong University [TPL1403]; PAPD fund

机构署名：

本校为其他机构

院系归属：

计算机科学与技术学院

摘要：

To overcome the deficiencies of weak local search ability in genetic algorithms (GA) and slow global convergence speed in ant colony optimization (ACO) algorithm in solving complex optimization problems, the chaotic optimization method, multi-population collaborative strategy and adaptive control parameters are introduced into the GA and ACO algorithm to propose a genetic and ant colony adaptive collaborative optimization (MGACACO) algorithm for solving complex optimization problems. The proposed MGACACO algorithm makes use of the exploration capability of GA and stochastic capability of ACO a...

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A novel collaborative optimization algorithm in solving complex optimization problems

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