• DocumentCode
    3002069
  • Title

    Elitist multiobjective evolutionary algorithm for environmental/economic dispatch

  • Author

    King, R.T.F.A. ; Rughooputh, Harry C S

  • Author_Institution
    Univ. of Mauritius, Mauritius
  • Volume
    2
  • fYear
    2003
  • fDate
    8-12 Dec. 2003
  • Firstpage
    1108
  • Abstract
    The environmental/economic dispatch problem is a multiobjective nonlinear optimization problem with constraints. Until recently, this problem has been addressed by considering economic and emission objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple Pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. We use an elitist multiobjective evolutionary algorithm based on the nondominated sorting genetic algorithm-II (NSGA-II) for solving the environmental/economic dispatch problem. Elitism ensures that the population best solution does not deteriorate in the next generations. Simulation results are presented for a sample power system.
  • Keywords
    Pareto optimisation; genetic algorithms; nonlinear systems; operations research; power generation dispatch; power generation economics; Elitist multiobjective evolutionary algorithm; Pareto-optimal solution; economic dispatch; environmental dispatch; nondominated sorting genetic algorithm; nonlinear optimization problem; Costs; Dispatching; Environmental economics; Evolutionary computation; Fuel economy; Hopfield neural networks; Linear programming; Power generation economics; Power system economics; Power system simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
  • Print_ISBN
    0-7803-7804-0
  • Type

    conf

  • DOI
    10.1109/CEC.2003.1299792
  • Filename
    1299792