一种结合Tabu搜索的非线性遗传算法研究

On nonlinear genetic algorithm based on Tabu search

利用Tabu搜索的强大局部搜索性能,提出一种新的非线性遗传算法.该方法将Tabu搜索技术内嵌于遗传算子中,构造了基于Tabu搜索的非线性杂交及变异算子,它能有效地提高算子的局部搜索能力,通过实例仿真证明了该算法的有效性;同时,以"平均截止代数"和"平均截止代数分布熵"作为评价指标,对该方法的优化效率进行研究,定量评价了该方法的优化效率,通过与实数遗传算法进行比较,说明了该方法的优化效率高于实数遗传算法.

Based on strong local search capability of Tabu search technique, a new nonlinear genetic algorithm (NGA) is proposed, and the nonlinear crossover and mutation operators are constructed based on Tabu search technique. The computational results indicate that the NGA has good performance and significantly improves the computational efficiency in optimization. 'The average truncated generations' and 'the distribution entropy of truncated generations' are used to optimization efficiency of NGA. The optimization efficiency of NGA is evaluated quantificationally. It is shown that the optimization efficiency of NGA is higher than that of real-coded genetic algorithm.