人工蜂群算法及其在组合优化中的应用研究

Artificial Bee Colony Algorithm and Its Application in Combinatorial Optimization

人工蜂群算法是一种启发式算法,通过模拟自然界蜂群觅食过程来解决现实中的优化问题。算法中将每只蜜蜂看做一个智能体,若干智能体间相互合作,高效地完成对目标的搜索、优化。总结人工蜂群算法用于解决组合优化问题的一般方法,以0-1背包问题为例对算法进行仿真测试,实验结果表明:人工蜂群算法有效且优于存在的蚁群算法。

Artificial Bee Colony Algorithm （ABC） is a new kind of heuristic algorithm. By simulating natural bee colony foraging process, this algorithm can solve practical problems. In this algorithm, every bee can be regarded as an agent. These agents can search and optimize the objectives efficiently by mutual cooperation. A general approach of Artificial Bee Colony Algorithm to solve combinatorial optimization problems has been presented. The simulation to 0-1 Knapsack Problem proves that ABC is superior to Ant Colony Algorithm.