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Optimization and profit distribution in a two-echelon collaborative waste collection routing problem from economic and environmental perspective

机译:经济和环境视角下的双梯队合作废物收集路线问题的优化与利润分布

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摘要

In order to reduce waste collection costs and realize sustainable urban development, this paper investigates a two-echelon collaborative waste collection vehicle routing problem (2E-CWCVRP), considering the cooperation and profit distribution between participants in the collection network. An optimization model for 2E-CWCVRP with the aim to minimize total costs and carbon emissions is constructed. Then, a three-stage solution approach is developed to solve this model, including a k-means clustering for simplifying the problem, and a hybrid heuristic for searching the optimal vehicle routes based on Clarke & Wright algorithm and an adaptive large neighborhood search algorithm (CW-ALNS). Finally, an improved Shapley value model is constructed for determining the costs and carbon emissions reduction amount and the best alliance sequence of each participant. The experiment results indicate that: (1) the effectiveness of CW-ALNS algorithm is verified through the benchmark instances; (2) the costs and carbon emissions of the collection network could be reduced simultaneously after the implementation of cooperation; (3) constructing a large collection and transfer network is more efficient than dividing the network into several individual parts. Finally, different alliance sequences are analyzed from the economics and environment perspective and the best alliance sequences are determined.
机译:为了降低废物收集成本并实现可持续城市发展,本文调查了两个梯度协作废物收集车辆路由问题(2E-CWCVRP),考虑到收集网络的参与者之间的合作和利润分配。建设了一种旨在最大限度地减少总成本和碳排放的2E-CWCVRP优化模型。然后,开发了一种三级解决方案方法来解决该模型,包括用于简化问题的K-means聚类,以及用于根据克拉克和赖特算法和自适应大邻域搜索算法搜索最佳车辆路线的混合启发式( CW-ALNS)。最后,构建了改进的福利值模型,用于确定每位参与者的成本和碳排放量和最佳联盟序列。实验结果表明:(1)通过基准实例验证CW-ALN算法的有效性; (2)合作后,收集网络的成本和碳排放可以同时减少; (3)构建大型收集和传输网络比将网络划分为几个单独的部分更有效。最后,从经济学和环境的角度分析不同的联盟序列,并确定最佳联盟序列。

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