李四兰 宋孟珂 郭伟钰



摘 要:低碳是我国今后相当长一段时期内经济可持续发展的必然要求,考虑到冷链物流在运输中的高能耗和高碳排放,本文将低碳理念引入到路径优化问题中,在传统的冷链多温共配车辆路径优化问题中加入碳排放成本,建立由运输成本、碳排放成本、制冷成本及损失成本构成的以总成本最低为目标函数的冷链物流多温共配路径优化模型。设计遗传算法,并用Matlab对案例进行求解,通过实例验证了模型的有效性和实用性。该模型可以为低碳环境下冷链物流企业的配送活动提供理论指导。
关键词:碳排放;多温共配;路径优化;遗传算法
中图分类号:U116.2 文献标识码:A
Abstract: Low carbon is an inevitable requirement for China's sustainable economic development for a long time to come, considering the high energy consumption and high carbon emissions of cold chain logistics in transportation, this paper introduces the concept of low carbon into the path optimization problem, carbon emission cost is added to the traditional multi-temperature co-allocation vehicle routing problem of cold chain, and a multi-temperature co-allocation vehicle routing optimization model of cold chain logistics is established with the lowest total cost consisting of transpor-tation cost, carbon emission cost, refrigeration cost and loss cost as the objective function. The genetic algorithm is designed, and the case is solved by Matlab. The effectiveness and practicability of the model are verified by an example. The model can provide theoretical guidance for the distribution activities of cold chain logistics enterprises in the low-carbon environment.
Key words: carbon emissions; multi-temperature co-allocation; path optimization; genetic algorithm
0 引 言
近年來冷链物流发展迅速,不同种类的产品在运输中对温度的要求也越来越高。多温共配可以同时提供不同温度要求的货物,但配送过程中的高能耗和高碳排放,与当下提倡的绿色低碳相悖,碳排放的增多不仅污染环境,而且由于国家碳税政策的实施也会使物流企业增加配送成本,所以把碳排放成本加入到运输的总成本中,确保产品在运输质量得到保障的前提下实现低碳运输,是冷链运输实践中物流配送亟待解决的问题。因此,对基于低碳排放的冷链多温共配路径优化问题进行研究具有重大实践意义。
在冷链物流路径优化问题方面,国内的研究主要集中在套用常规的模型及算法解决配送问题,陈磊等(2015)[1]、李畅等(2019)[2]、康凯等(2019)[3]在考虑时间窗、随机环境及不同车型的条件下,建立总成本最小化的路径优化模型,并采用常用的遗传算法、蚁群算法、模拟退火算法等方法解决此类问题。……