• DocumentCode
    296186
  • Title

    An integrated framework for devising optimum generation schedules

  • Author

    Srinivasan, Dipti ; Tettamanzi, Andrea G B

  • Volume
    1
  • fYear
    1995
  • fDate
    Nov. 29 1995-Dec. 1 1995
  • Firstpage
    1
  • Abstract
    An integrated framework for generating optimum unit commitment and dispatch schedules is presented in this paper. The work reported here employs a hybrid technique by which a genetic population can be confined to a set of feasible solutions. Heuristics are used to ensure that all the constraints, both linear and nonlinear, are fulfilled for each member of the population. The use of this technique, which combines the advantages of knowledge-based methods with the strengths of evolutionary algorithms, results in considerable reduction in computing time, making its application viable in daily operation scheduling
  • Keywords
    Constraint optimization; Costs; Evolutionary computation; Genetic algorithms; Job shop scheduling; Lagrangian functions; Optimal scheduling; Power generation; Processor scheduling; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1995., IEEE International Conference on
  • Conference_Location
    Perth, WA, Australia
  • Print_ISBN
    0-7803-2759-4
  • Type

    conf

  • DOI
    10.1109/ICEC.1995.489109
  • Filename
    489109