一种基于信息熵调整的自适应蚁群算法
n Adaptive Ant Colony Algorithm based on Information Entropy
针对基本蚁群算法在求解大规模旅行商问题易导致搜索时间过长或陷入停滞的问题，提出一种基于信息熵调整的自适应蚁群算法。该算法通过优化过程中种群的信息熵来衡量演化的程度，自适应地调整路径选择策略和信息素更新策略。信息熵的计算以某条路径边上的信息素占总信息素量的比例为基础。通过对大规模城市数旅行商问题的实验，结果表明提出的基于信息熵调整的自适应蚁群算法比基本蚁群算法获得更好的解，并且增加了算法的稳定性。
o solve the premature convergence problem of the basic ant colony algorithm, a self-adaptive ant colony algorithm based on information entropy is proposed. By using the population's entropy to evaluate the evolution state, the algorithm adjusts the path selection strategy and the pheromone updating strategy adaptively. Experimental results on TSP of large cities show that the improved algorithm proposed has better solution and higher stability than the basic ant colony system does.
肖菁、李亮平
计算技术、计算机技术
蚁群算法信息熵自适应蚁群算法旅行商问题组合优化问题
ant colony algorithminformation entropyself-adaptive ant colony algorithmtraveling salesman problemcombinatorial optimization problem
肖菁,李亮平.一种基于信息熵调整的自适应蚁群算法[EB/OL].(2010-08-31)[2025-08-23].http://www.paper.edu.cn/releasepaper/content/201008-483.点此复制
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