关键词: 萤火虫优化（GSO）, 早熟收敛, 混沌, 车辆路径问题（VRP）, 切比雪夫映射

Abstract: To overcome the disadvantages of premature convergence, local optimum and low precision in basic glowworm swarm optimization (GSO) algorithm, this paper proposes a chaotic glowworm swarm optimization (CGSO) algorithm based on Chebyshev map. CGSO applies the features of chaotic randomness and ergodicity to initial the glowworm population. Therefore, it can achieve high quality and uniformly distributed initial solutions. Meanwhile, in order to increase the diversity of population, the proposed algorithm disturbs the partial individuals with low fitness value by Chebyshev map. The experiments on four standard test functions show that CGSO outperforms the basic GSO in precision and global searching ability. Finally, the improved algorithm is applied to vehicle routing problem (VRP), the results show that the algorithm is effective.

Key words: glowworm swarm optimization (GSO), premature convergence, chaos, vehicle routing problem (VRP), Chebyshev map