A hybrid ant colony optimization approach based local search scheme for multiobjective design optimizations

被引：25

作者：

Mousa, A. A. ^{[1
,2
]}

Abd El-Wahed, Waiel F. ^{[3
]}

Rizk-Allaha, R. M. ^{[1
]}

机构：

[1] Minoufia Univ, Fac Engn, Dept Basic Engn Sci, Shibin Al Kawm, Egypt

[2] Taif Univ, Fac Sci, Dept Math, At Taif, Saudi Arabia

[3] Minoufia Univ, Fac Comp & Informat, Dept Operat Res, Shibin Al Kawm, Egypt

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 2011年 / 81卷 / 04期

关键词：

Ant colony optimization; Design; Multiobjective optimization; Multipheromone; Local search approach; Steady state genetic algorithm; ALGORITHMS;

D O I：

10.1016/j.epsr.2010.12.005

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents an optimal design of a linear motor considering two objective functions namely. maximum force and minimum saturation and design of air-cored solenoid with maximum inductance and minimum volume as the objective functions. The proposed approach differs from the traditional ones in its design of a multipheromone ant colony optimization (MACO) as well as the inclusion of steady state genetic algorithm (SSGA) and local search approach. Detailed numerical results on different multiobjective design applications are reported. The results obtained by our implementation substantiate the success of this new approach. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：1014 / 1023

页数：10

共 25 条

[1] Ant colony optimization for multi-objective optimization problems [J].

Alaya, Ines ;

Solnon, Christine ;

Ghedira, Khaled .

19TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL I, PROCEEDINGS, 2007, :450-457

[2] Sensitivity analysis applied to decision making in multiobjective evolutionary optimization [J].

Avila, SL ;

Lisboa, AC ;

Krähenbühl, L ;

Carpes, WP ;

Vasconcelos, JA ;

Saldanha, RR ;

Takahashi, RHC .

IEEE TRANSACTIONS ON MAGNETICS, 2006, 42 (04) :1103-1106

[3] Pareto optimality and particle swarm optimization [J].

Baumgartner, U ;

Magele, C ;

Renhart, W .

IEEE TRANSACTIONS ON MAGNETICS, 2004, 40 (02) :1172-1175

[4] An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP) [J].

Chaharsooghi, S. K. ;

Kermani, Amir H. Meimand .

APPLIED MATHEMATICS AND COMPUTATION, 2008, 200 (01) :167-177

[5]

DESHPANDE AD, 2001, LINEAR ELECT DRIVE U

[6]

DESHPANDE AD, 2000, THESIS U MASSACHUSET

[7] An improved technique for enhancing diversity in Pareto evolutionary optimization of electromagnetic devices [J].

Di Barba, P ;

Farina, M ;

Savini, A .

COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2001, 20 (02) :482-496

[8] Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection [J].

Doerner, K ;

Gutjahr, WJ ;

Hartl, RF ;

Strauss, C ;

Stummer, C .

ANNALS OF OPERATIONS RESEARCH, 2004, 131 (1-4) :79-99

[9] Ant algorithms for discrete optimization [J].

Dorigo, M ;

Di Caro, G ;

Gambardella, LM .

ARTIFICIAL LIFE, 1999, 5 (02) :137-172

[10] Ant system: Optimization by a colony of cooperating agents [J].

Dorigo, M ;

Maniezzo, V ;

Colorni, A .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1996, 26 (01) :29-41

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