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The paper deals with the performance of genetic algorithm according to the analysis of control parameters, the evolution between different sub-populations, the interaction on best individual and, the expansion on the search interval, are analyzed, and an adaptive genetic algorithm is presented, which is multi-population parallel evolutionary and variable population size. It is proved by comparative...
Based on Chaotic Genetic Algorithm idea, this paper presents a new solution for the classic Knapsack Problem(KP). We introduce Chaos idea into Genetic Algorithm, adding the disturbance to help finding better solutions in the traditional Genetic Algorithm. Results of numerical tests show that it has high efficiency and the good ability of global optimization.
A hybrid simplex-genetic algorithm (HSGA) is presented to solve global numerical optimization problems. The HSGA combines the traditional genetic algorithm, which has a powerful global exploration capacity, with simplex algorithm, which can exploit the local range. Some improved mechanism are introduced in the HSGA, such as hybrid encoding, orthogonal design, and feedback mutation etc. so the HSGA...
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