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基于超启发式算法的选址-路径问题研究
Research on location-routing problem based on hyper-heuristic algorithm
【摘要】 为了降低物流配送过程中车辆的碳排放,采用具有良好通用性的超启发式算法对低碳选址路径问题进行求解。将蛙跳算法作为超启发式算法的高层选择策略,并在蛙跳算法中提出了基于最长公共子序列的相似度计算方式代替原有的相似度计算,而采用动态规划的方法对个体间的最长公共子序列进行计算。实验结果表明:提出的相似度计算方式能更直观地反映个体之间的相似性,具有良好的通用性,并且在低碳选址-路径问题上获得更优秀的解。
【Abstract】 In order to reduce the carbon emission of vehicles, the hyper-heuristic algorithm with good universality is used to solve the low-carbon location-routing problem. This paper uses leapfrog algorithm as the top choice strategy of hyper-heuristic algorithms, and proposes the similarity calculation method based on longest common subsequence instead of the original similarity calculation in leapfrog algorithm, and uses the dynamic programming to calculate the longest common subsequence between individuals. The experimental results show that the new similarity calculation method can more intuitively reflect the similarities between individuals, and it makes hyper-heuristic algorithm get better solutions in location-routing problem.
【Key words】 hyper-heuristic algorithm; selection strategy; leapfrog algorithm; longest common subsequence;
- 【文献出处】 浙江工业大学学报 ,Journal of Zhejiang University of Technology , 编辑部邮箱 ,2019年06期
- 【分类号】F252;TP18
- 【被引频次】2
- 【下载频次】564