关键词: 群居蜘蛛优化算法, 多种群, 多峰函数优化, 自适应, 回溯

Abstract: An Adaptive Multi-swarm Backtracking Social Spiders Optimization(AMBSSO) is proposed to solve the complex multimodal function optimization problems of Social Spiders Optimization（SSO） algorithm which has low success rate and convergence precision. The adaptive decision radius is introduced in SSO algorithm to improve the sample population diversity. The spider population is dynamically divided into multiple populations.  Individual spider takes different updating ways according to its fitness. The backtracking evolution strategy is put forward to ensure global searching ability and it is carried out according to evolutionary level based on the selection of global extremum of function. The simulation results show that AMBSSO algorithm has faster convergence speed and higher convergence precision, especially for high-dimensional and multimodal function optimization problems, compared with SSO, PSO and other optimization algorithms.

Key words: social spider optimization algorithm, multi-swarm, multimodal function optimization, adaptation, backtracking