Abstract: A hyper heuristic algorithm of ant colony selection mechanism was proposed to solve the problem of low carbon location routing problem with capacity constraint,and the ant colony selection mechanism was chosen as a hyper heuristic selection.The ant colony selection strategy was optimized,then the different high-level strategies were compared and analyzed to get the optimal effect of Only Improvement(OI) acceptance criterion.In addition,compared with other algorithms,the validity of algorithm was tested and compared with the least carbon emission and the minimum cost.The experimental analysis showed that the location-path model of carbon emission could reduce the carbon emission effectively.

Key words: location-routing problem, carbon emission, hyper-heuristic algorithm, ant colony selection strategy

摘要： 针对有容量约束的低碳选址—路径问题,提出一种基于蚁群选择机制的超启发算法用于模型求解,即将蚁群选择机制作为超启发算法的选择策略。首先对蚁群选择策略进行参数寻优,将高层策略进行对比实验分析得出最优的接受准则,即只接受好解(OI),并与得到的蚁群选择策略参数进行优化组合。此外,与其他算法的对比实验验证了所提算法的有效性。最后分别对以最少碳排放量和最小成本为目标的模型进行求解分析对比,结果表明考虑碳排放的选址—路径模型可以有效减少碳排放量。

关键词: 选址&mdash, 路径问题, 二氧化碳排放, 超启发算法, 蚁群选择策略