Abstract: With the acceleration of urbanization and rapid economic development, the quantity of municipal solid waste has shown a trend of rapid growth, and an efficient collection of municipal solid waste has become an urgent task for the sanitation industry. At the same time, in order to effectively control and reduce greenhouse gas emissions from transportation, countries around the world have formulated and implemented sustainable energy saving and emission reduction policies. This puts strict requirements on municipal solid waste collection, and also brings pressure to reduce emissions. On the other hand, high collection costs are also a major obstacle limiting an efficient management of municipal solid waste. With the growth of waste volume, an increase in collection costs has become more and more prominent, and waste disposal companies have to invest more resources in coping with the huge demand for waste collection. Faced with the double pressure of cost reduction and emission control, municipal solid waste management departments have tried to save energy and increase efficiency by adopting various optimization methods, such as the Municipal Solid Waste Vehicle Route Problem (MSWVRP). As the public attaches more importance to environmental protection, scholars’ research on MSWVRP has expanded from focusing only on economic costs to taking environmental benefits into account, and then the green MSWVRP problem has been proposed.
With the enhanced promotion and application of new energy vehicles in the sanitation field, the green MSWVRP is no longer limited to the pollution problem of fuel vehicles, but the research on the MSWVRP based on electric vehicles, the Municipal Solid Waste Electric Vehicle Routing Problem (MSWEVRP), is gradually carried out. However, the current research on MSWEVRP by scholars at home and abroad considers charging strategies in a simplistic way, mostly focusing on the complete charging behavior, a single charging mode, or even ignoring the charging problem, and most of it focuses on the first-echelon collection process as the scope of the research, and is lack of the exploration for the full collection process in the two-echelon mode. Therefore, this paper adopts the hybrid scheme of using electric vehicles for the first echelon of collection and fuel vehicles for the second echelon for the two-echelon waste collection mode. Meanwhile, the focus is on EV charging strategies, including partial charging behavior and multiple charging modes, which are incorporated into the model construction and algorithm design. Fusing the ideas of adaptive strategies, local search and large neighborhood search algorithms, the hybrid adaptive large neighborhood search algorithm (HALNS) is proposed, and the charging station related operator and charging mode related operator that fit the problem are also designed to accelerate the convergence and thus improve the quality of the solution.
This study takes Chaoyang District of Beijing, China as an example, constructs an arithmetic example and successively carries out model accuracy test, algorithm validity verification and performance comparison, as well as case solving and result analysis. The results show that the two-echelon waste collection mode, partial charging behavior and multiple charging mode can effectively reduce the waste collection cost. Compared with the full charging behavior, the partial charging behavior can significantly save the collection costs, with an improvement of up to 10.36%. Multi-charging reduces collection costs by 1.42% compared to single (slow) charging. A two-echelon mode using both electric vehicle collection and fuel vehicle collection can reduce cost by 67.86% compared to a direct collection mode using only fuel vehicles.
In summary, this paper proposes the optimization problem of municipal solid waste collection routing considering charging strategy in two-echelon mode, in-depth investigation into partial charging behavior and multiple charging modes in charging strategy. It can improve the availability and economy of electric vehicles and provide a routing plan for cost reduction and emission control for the municipal solid waste collection. Our study is of great significance for improving the level of waste management and promoting the sustainable development of the city.

Key words: urban traffic, electric vehicle routing problem, adaptive large neighborhood search algorithm, municipal solid waste collection, charging strategy

摘要： 面对减排与降本的双重压力,城市生活垃圾管理部门开始使用电动车完成收运任务。首先,本文基于两级垃圾收运模式,采用第一级收运使用电动车,第二级使用燃油车的混合方案,考虑包含部分充电行为和多充电模式的灵活充电策略,建立带有时间窗的车辆路径优化模型。其次,针对充电特性设计邻域操作算子,包括充电站移除和插入算子以及充电模式调整算子,提出混合自适应大邻域搜索算法,并通过参数调整寻优与性能对比完成提出算法的有效性验证。最后,以北京市朝阳区为例进行算例分析,对比不同充电策略下的收运成本,结果表明,相较完全充电行为,部分充电行为能够节约10.36%的收运成本;多充电模式较单一慢速充电模式可减少1.42%的收运成本。相比于只采用燃油车的直接收运模式,使用电动车和燃油车收运的两级模式可使收运成本降低32.14%。

关键词: 城市交通, 电动车辆路径问题, 自适应大邻域搜索算法, 城市生活垃圾收运, 充电策略