| Summary: | 碩士 === 國立臺灣海洋大學 === 機械與機電工程學系 === 94 === Genetic algorithm is a global searching way for the optimal solution, but it will trapped in the local solution easily. When the searching values approaches the optimal solution, we need change searching step a half, otherwise the update value will far away from the optimal solution. In this paper, we presented that when the value approaching the optimal solution, we set all searching parameters at some interval, and then using the chromosome’s arrayal character to search the optimal solution fast. First, the value is encoded by binary and fit N bits from left of the string, and then divided any blocks. After j generations, we will find out the interval of suitable value, and choose the half interval. Then parameter solving interval diminish it, repeat the same steps iterately until it converges to the optimal value solution. The simulation results shown that hybrid general genetic algorithm and interval-reduction genetic algorithm will search fast optimal solution exactly.
keywords: genetic algorithm, binary, binomial, optimal solution.
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