摘要
根据群集智能优化原理,给出了一种基于萤火虫寻优思想的新算法———萤火虫群优化算法,并针对0-1背包问题进行求解。经仿真实验并与蜂群算法、蚁群算法和微粒群算法进行了比较,获得了满意的结果,这说明了算法在0-1背包问题求解上的有效性和具有更快的收敛速度,拓展了萤火虫群优化算法的应用领域。
According to the principle of swarm intelligence, this paper proposed a new optimization algorithm based on the ideas of glowworms :the glowworm swarm optimization (GSO) algorithm to solve the 0-1 knapsack problem. Through the numerical simulations, it compared with that of artificial bee colony algorithm, ant colony optimization algorithm and particle swarm optimization. And it obtains the satisfactory results,which show the validity and effectiveness of the algorithm,expands the applications of GSO.
出处
《计算机应用研究》
CSCD
北大核心
2013年第4期993-994,998,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(70871081)
上海市研究生创新基金资助项目(JWCXSL1202)
关键词
萤火虫群优化算法
0-1背包问题
组合优化
群集智能
glowworm swarm optimization algorithm
0-1 knapsack problem
combinatorial optimization
swarm intelligence