• DocumentCode
    2976416
  • Title

    A new evolutionary programming approach based on simulated annealing with local cooling schedule

  • Author

    Cho, Hyeon-Joong ; Oh, Se-young ; Choi, Doo-Hyun

  • Author_Institution
    Dept. of Electr. Eng., Pohang Univ. of Sci. & Technol., South Korea
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    598
  • Lastpage
    602
  • Abstract
    The NPOSA (New Population-Oriented Simulated Annealing) technique is introduced as an efficient global search tool to solve optimization problems. Unlike the conventional simulated annealing or its hybrid algorithms, each individual in the population can intelligently plan its own annealing schedule in an adaptive fashion to the given problem at hand. This not only enhances the search speed but furthermore yields a solution near the global optimum. This technique has been applied to solve the traveling salesman problem (TSP) for combinatorial optimization, as well as a continuous function optimization problem, to demonstrate its validity and effectiveness
  • Keywords
    functional analysis; genetic algorithms; planning (artificial intelligence); programming; scheduling; search problems; simulated annealing; travelling salesman problems; NPOSA; adaptive planning; combinatorial optimization; continuous function optimization; evolutionary programming; global optimum; global search tool; intelligent annealing schedule planning; local cooling schedule; population-oriented simulated annealing; search speed; traveling salesman problem; Adaptive scheduling; Costs; Electronic mail; Electronics cooling; Genetic programming; Scheduling algorithm; Simulated annealing; Solids; Temperature distribution; Traveling salesman problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-4869-9
  • Type

    conf

  • DOI
    10.1109/ICEC.1998.700096
  • Filename
    700096