Four techniques are described which can help a genetic algorithm to locate multiple approximate solutions to a multi-modal optimization problem. These techniques are: fitness sharing, ‘eliminating’ identical solutions, ‘removing’ acceptable solutions from the reproduction cycle and applying heuristics to improve sub-standard solutions. Essentially, all of these techniques operate by encouraging genetic variety in the potential solution set. The preliminary design of a gearbox is presented as an example to illustrate the effectiveness of the proposed techniques.


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    Title :

    Optimization of Multi-Modal Discrete Functions Using Genetic Algorithms


    Contributors:
    Pham, D T (author) / Yang, Y (author)


    Publication date :

    1993-01-01


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Optimization of multi-modal discrete function using genetic algorithms

    Pham,D.T. / Yang,Y. / Univ.of Wales College of Cardiff,School of Electrical, Electronic and Systems Engng.,GB | Automotive engineering | 1993


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