Multi-Population Parallel Imperialist Competitive Algorithm for Solving Systems of Nonlinear Equations

被引：0

作者：

Majd, Amin ^{[1
]}

Abdollahi, Mandi ^{[2
]}

Sahebi, Golnaz ^{[1
]}

Abdollahi, Davoud ^{[3
]}

Dancshtalab, Masoud ^{[4
]}

Plosila, Juha ^{[1
]}

Tenhunen, Hannu ^{[5
,6
]}

机构：

[1] Univ Turku, Dept Informat Technol, Turku, Finland

[2] Univ Tabriz, Dept Comp Sci, Tabriz, Iran

[3] Univ Coll Daneshvaran, Dept Math Sci, Tabriz, Iran

[4] Royal Inst Technol KTH, Stockholm, Sweden

[5] Royal Inst Technol, Stockholm, Sweden

[6] Univ Turku, SF-20500 Turku, Finland

来源：

2016 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2016) | 2016年

关键词：

parallel imperialist competitive algorithm (PICA); multi-population technique; evolutionary computing (EC); super linear performance; nonlinear equations; multi objective optimization; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

the widespreadimportance of optimization and solving NP-hard problems, like solving systems of nonlinear equations, is indisputable in a diverse range of sciences. Vast uses of non-linear equations are undeniable. Some of their applications are in economics, engineering, chemistry, mechanics, medicine, and robotics. There are different types of methods of solving the systems of nonlinear equations. One of the most popular of them is Evolutionary Computing (EC). This paper presents an evolutionary algorithm that is called Parallel Imperialist Competitive Algorithm (PICA) which is based on a multi population technique for solving systems of nonlinear equations. In order to demonstrate the efficiency of the proposed approach, some well-known problems are utilized. The results indicate that the PICA has a high success and a quick convergence rate.

引用

页码：767 / 775

页数：9

共 50 条

[31] A multi-population genetic algorithm approach for solving ill-posed problems
N. S. Mera
L. Elliott
D. B. Ingham
Computational Mechanics, 2004, 33 : 254 - 262
[32] Particle swarm algorithm for solving systems of nonlinear equations
Jaberipour, Majid
Khorram, Esmaile
Karimi, Behrooz
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 62 (02) : 566 - 576
[33] Multi-Population Parallel Wolf Pack Algorithm for Task Assignment of UAV Swarm
Lu, Yingtong
Ma, Yaofei
Wang, Jiangyun
APPLIED SCIENCES-BASEL, 2021, 11 (24):
[34] PARALLEL METHODS FOR SOLVING NONLINEAR BLOCK BORDERED SYSTEMS OF EQUATIONS
ZHANG, XD
BYRD, RH
SCHNABEL, RB
SIAM JOURNAL ON SCIENTIFIC AND STATISTICAL COMPUTING, 1992, 13 (04): : 841 - 859
[35] A multi-population genetic algorithm to solve multi-objective scheduling problems for parallel machines
Cochran, JK
Horng, SM
Fowler, JW
COMPUTERS & OPERATIONS RESEARCH, 2003, 30 (07) : 1087 - 1102
[36] Heterogeneous Multi-Population Cultural Algorithm
Raeesi, Mohammad R. N.
Kobti, Ziad
2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2013, : 292 - 299
[37] Parallel implementation of multi-population differential evolution
Zaharie, D
Petcu, D
CONCURRENT INFORMATION PROCESSING AND COMPUTING, 2005, 195 : 223 - 232
[38] Multi-Satellite Mission Planning based on Multi-population Cooperative Parallel Evolutionary Algorithm
Li, Hui
Zhao, Man
Zhang, Chenglu
Mo, Dengfeng
2021 21ST INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY COMPANION (QRS-C 2021), 2021, : 584 - 588
[39] Solving a multi-product distribution planning problem in cross docking networks: An imperialist competitive algorithm
Shima Javanmard
Behnam Vahdani
Reza Tavakkoli-Moghaddam
The International Journal of Advanced Manufacturing Technology, 2014, 70 : 1709 - 1720
[40] Solving a multi-product distribution planning problem in cross docking networks: An imperialist competitive algorithm
Javanmard, Shima
Vahdani, Behnam
Tavakkoli-Moghaddam, Reza
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2014, 70 (9-12): : 1709 - 1720

← 1 2 3 4 5 →