关键词: 布谷鸟搜索算法, 反方向视角, 二项交叉, 函数优化问题

Abstract: Cuckoo search algorithm is a new nature-inspired optimization technique, which uses Lévy Flights random walk and Biased random walk to search new solutions iteratively. In Lévy Flights random walk, all individuals search new solutions around the best solution obtained so far. This may easy make the population converge to the best one. To avoid converging to the current optimal solution, this paper uses the reverse direction angle strategy to search new solutions probably, and proposes a cuckoo search algorithm with reverse direction angle and binomial crossover, called RBCS. In RBCS, a binomial crossover strategy is employed to enhance the search ability of Biased random walk. Compared with the standard cuckoo search algorithm, the experimental results show that the proposed strategies can improve the convergence speed and the solution quality of the algorithm for the continuous function optimization problems effectively. Compared with other improved cuckoo search algorithms and other evolutionary algorithms, the experimental results reveal that the proposed algorithm is competitive for the continuous function optimization problems.

Key words: cuckoo search algorithm, reverse direction angle, binomial crossover, function optimization problems