• 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