Management Science and Real Estate School, Chongqing University, Chongqing, China.
Management Science and Real Estate School, Chongqing University, Chongqing, China.
Sci Total Environ. 2021 Mar 1;758:144062. doi: 10.1016/j.scitotenv.2020.144062. Epub 2020 Nov 26.
In recent years, production and consumption activities carried out in accordance with the "take-make-dispose" process have caused environmental damage and resource waste. Reverse logistics based on the concept of "sustainable development and circular economy" has gained public attention, including the recycling and reuse of recyclable wastes. In order to explore the impact of recyclable wastes transportation on cost, environment and resources, this paper focuses on a vehicle routing problem considering electric heterogeneous fleet for a two-echelon recycling network, recycling stations and recycling centers. With the goal of minimizing the total cost, a recycling heterogeneous fleet electric vehicle routing model with time windows is established under the consideration of vehicle load constraints, vehicle type constraints on the weight of loaded recyclable wastes and customer's allowable service time constraints. For carbon emissions reduction and environment protection, vehicles used in recycling stations are designated as electric vehicles. Then, a hybrid genetic algorithm with a large-scale neighborhood search algorithm is proposed. Finally, numerical experiments are conducted on vehicle types in recycling stations, and the computational results show the use of heterogeneous fleets could reduce costs. By analyzing the relationship between customer service time and total cost, the best service time rule could be obtained in the case of customer satisfaction. Meanwhile, by analyzing the relationship between the number and the loading capacity of electric vehicles in recycling stations and total cost, the best number and the loading capacity of electric vehicles could be obtained. This heterogeneous fleet recyclables collection routing model can greatly support the construction of recycling centers and the planning of recycling tasks, and provide a basis for recycling companies to deal with the relationship between economy, environment and resources.
近年来，按照“取-用-弃”流程进行的生产和消费活动造成了环境破坏和资源浪费。基于“可持续发展和循环经济”理念的逆向物流引起了公众的关注，其中包括可回收废物的回收和再利用。为了探讨可回收废物运输对成本、环境和资源的影响，本文针对具有时间窗的考虑电动异质车队的两级回收网络、回收站和回收中心的车辆路径问题进行了研究。本文以总成本最小化为目标，在考虑车辆载重量约束、车辆类型对装载可回收废物重量的约束和客户允许服务时间约束的情况下，建立了带时间窗的回收异质车队电动汽车路径模型。为了减少碳排放和保护环境，回收站使用的车辆被指定为电动汽车。然后，提出了一种混合遗传算法与大规模邻域搜索算法。最后，对回收站的车辆类型进行了数值实验，计算结果表明使用异质车队可以降低成本。通过分析客户服务时间与总成本之间的关系，可以在满足客户满意度的情况下获得最佳的服务时间规则。同时，通过分析回收站中电动汽车的数量和载重量与总成本之间的关系，可以获得最佳的电动汽车数量和载重量。这种异质车队可回收物收集路径模型可以极大地支持回收中心的建设和回收任务的规划，为回收公司处理经济、环境和资源之间的关系提供了依据。
