考虑碳排放的选址-路径问题研究

Research on location routing problem considering carbon emissions

针对物流配送中的选址-路径问题,在车辆路径安排时加入了碳排放的考虑,建立了包含碳排放、配送成本和客户满意度的多目标优化模型,提出了一种基于禁忌搜索的超启发式算法.在超启发式算法的框架中,构建了一系列基于问题特征的底层启发式算子,设计了禁忌搜索作为高层启发式策略.以某地区物流配送实例进行仿真实验,通过超启发式算法和NSGA-II算法比较证明,所提算法可以更好地解决选址路径的多目标问题,能较快地找到更优解,达到较高的搜索效率和算法稳定性.与传统的启发式算法相比,该算法具有很好的通用性,可以很容易推广到其他选址-路径变种问题上.

Aiming at the optimization of location routing problem in logistics distribution,a multi-objective optimization model including carbon emission,distribution cost and customer satisfaction is established,a tabu search based hyper heuristic algorithm is proposed.In the framework of hyper heuristic algorithm,a series of low level heuristics based on the problem features are constructed,and tabu search is designed as a high level strategy.Compared with the NSGA-II algorithm,the multi-objective problem of location routing problem can be solved better with the hyper heuristic algorithm,and the better solution can be found quickly,and higher search efficiency and stability of the algorithm can be achieved.Compared with the traditional heuristic algorithms,this algorithm has good versatility,and can be easily extended to other location routing problem variants.