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A Heuristic Method for Integer Programming using Discrete Hybrid Evolutionary Algorithm |
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PP: 3191-3200 |
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Author(s) |
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Hong Li,
Li Zhang,
Yong-Chang Jiao,
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Abstract |
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| A discrete hybrid evolutionary algorithm is developed to solve global numerical optimization problems with discrete
variables. In this algorithm, the orthogonal experimental design acts as the crossover operator to achieve crossover, and the migration
operator is employed to keep the population’s diversity. In addition, the simplified quadratic interpolation method is taken as a local
search operator, which is adopted to improve the algorithm’s local search ability. Moreover, a few of foreign chromosomes, which are
generated via randomly perturbing the best candidate chromosome in the current population, are introduced into the next generation to
avoid most of chromosomes gradually clustering around the best candidate chromosome in some subsequent generations. A rounding
and truncation procedures is incorporated in the operations of the algorithm to ensure that the integer restrictions and box constraints
are satisfied. Numerical experiments on 22 test problems have demonstrated the efficiency of the proposed method. |
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