DocumentCode :
2329324
Title :
Maximin spreading algorithm
Author :
Pires, E. J Solteiro ; Mendes, Luís ; Lopes, António M. ; de Moura Oliveira, P.B. ; Machado, J. A Tenreiro ; Vaz, João ; Rosário, Maria J.
Author_Institution :
Centro de Investigacao e de Tecnol. Agro-Ambientais e Biologicas, Univ. de Tras-os-Montes e Alto Douro, Vila Real, Portugal
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents a genetic algorithm to optimize uni-objective problems with an infinite number of optimal solutions. The algorithm uses the maximin concept and e-dominance to promote diversity over the admissible space. The proposed algorithm is tested with two well-known functions. The practical results of the algorithm are in good agreement with the optimal solutions of these functions. Moreover, the proposed optimization method is also applied in two practical real-world engineering optimization problems, namely, in radio frequency circuit design and in kinematic optimization of a parallel robot. In all the cases, the algorithm draws a set of optimal solutions. This means that each problem can be solved in several different ways, all with the same maximum performance.
Keywords :
genetic algorithms; network synthesis; robot kinematics; e-dominance; genetic algorithm; kinematic optimization; maximin spreading algorithm; parallel robot; radio frequency circuit design; real-world engineering optimization problems; uniobjective problem optimization; Algorithm design and analysis; Electronic mail; Heuristic algorithms; Kinematics; Manipulators; Optimization; Switching circuits;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
Type :
conf
DOI :
10.1109/CEC.2010.5586236
Filename :
5586236
Link To Document :
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