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Collaborative logistics pickup and delivery problem with eco-packages based on time-space network

机译:基于时空网络的生态包装协作物流拾音和交付问题

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摘要

Collaboration among logistics companies offers a simple and effective way of increasing logistics operation efficiency. This study designs an optimal collaboration strategy by solving the collaborative logistics pickup and delivery problem with eco-packages (CLPDPE). This problem seeks to minimize the total operational costs by forming collaborative alliances and allocating trucking resources based on time?space (TS) network properties. The synchronization of two-echelon logistics networks is improved by solving this problem. Moreover, this study considers the stability of collaboration (i.e., the willingness of logistics companies to join and remain in collaborative alliances) by comparing different profit allocation strategies in the CLPDPE solving process. A novel methodology that combines multi-objective mixed integer programming, multidimensional K-means clustering, reference point based non-dominated sorting genetic algorithm-II (RP-NSGA-II), forward dynamic programming and improved Shapley value method is developed to formulate and solve CLPDPE. Our results show that the proposed algorithm outperforms most other algorithms in minimizing the total cost, waiting time and number of vehicles. An empirical case study in Chongqing city, China suggests that the proposed collaborative mechanism and transportation resource sharing strategy based on TS network can reduce cost, improve distribution efficiency, and contribute to efficient, smart, intelligent and sustainable urban logistics and transportation systems.
机译:物流公司之间的合作提供了一种简单而有效的,即增加物流运营效率。本研究通过解决生态包(CLPDPE)解决协作物流拾取和交货问题,设计了最佳协作策略。此问题旨在通过形成基于时间的协作联盟和分配货运资源来最大限度地减少总运营成本?空间(TS)网络属性。通过解决这个问题,改善了双梯级物流网络的同步。此外,本研究考虑了合作的稳定性(即,物流公司的意愿,通过比较CLPDPE解决过程中的不同利润分配策略来加入和留在协作联盟中的愿望。一种新的方法,即结合多目标混合整数编程,多维k均值聚类,参考点基于非主导的分类遗传算法-II(RP-NSGA-II),正向动态编程和改进的福芙值方法是制定和的解决CLPDPE。我们的研究结果表明,该算法在最大限度地降低总成本,等待时间和车辆数量方面优于大多数其他算法。中国重庆市的实证案例研究表明,基于TS网络的拟议协作机制和运输资源共享战略可以降低成本,提高分配效率,有助于高效,智能,智能化,可持续的城市物流和运输系统。

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