启发式
蚁群优化算法
数学优化
趋同(经济学)
车辆路径问题
计算机科学
整数规划
概率逻辑
布线(电子设计自动化)
蚁群
极值优化
算法
元启发式
元优化
数学
人工智能
计算机网络
经济
经济增长
作者
Tinglei Pan,Haipeng Pan,Jingfei Gao
标识
DOI:10.1109/chicc.2015.7260059
摘要
The vehicle routing problem is a classical combinatorial optimization and integer programming problem. This paper proposed an improved ant colony algorithm to avoid the premature convergence and increase convergence speed, its main improvements including a novel probabilistic state transition, dynamically adjusting the value of the pheromone volatile parameter, and coupled with local optimization heuristics(2-Opt heuristics). Apply this algorithm to instance Eil22, the result shows that the proposed algorithm can obtain the optimal solution rapidly and accurately.
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