Ant Colony Optimization Based on Adaptive Volatility Rate of Pheromone Trail

• 作者: Han HUANG Xianheng MA Yong QIN Zhaoquan CAI
• 来源期刊: 通讯、网络与系统学国际期刊(英文)
• 学科: 医学
• 关键词: Ant COLONY Optimization (ACO) ADAPTIVE VOLATILITY RATE PHEROMONE TRAIL
• 年，卷（期）: 2009,（8）
• 页码范围: 792-796
• 页数: 5页
• 分类号: R73

摘要

Ant colony optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. The volatility rate of pheromone trail is one of the main parameters in ACO algorithms. It is usually set experimentally in the literatures for the application of ACO. The present paper first proposes an adaptive strategy for the volatility rate of pheromone trail according to the quality of the solutions found by artificial ants. Second, the strategy is combined with the setting of other parameters to form a new ACO method. Then, the proposed algorithm can be proved to converge to the global optimal solution. Finally, the experimental results of computing traveling salesman problems and film-copy deliverer problems also indicate that the proposed ACO approach is more effective than other ant methods and non-ant methods.