基于仿真的超级互联大城市包裹物流评估

Logistics Pub Date : 2024-07-02 DOI:10.3390/logistics8030066
Sara Kaboudvand, Benoit Montreuil
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引用次数: 0

摘要

背景:超级互联特大城市包裹物流(HMPL)的概念于 2018 年提出,旨在提高特大城市包裹运输的效率、响应能力、弹性和可持续性。然而,评估此类根本性解决方案存在挑战,需要全面了解所有利益相关者和相关决策。方法:本研究引入了一个基于离散事件代理的模拟平台,该平台涵盖了重要的利益相关者,并解决了不同层次的决策问题。该平台为评估 HMPL 结构中的关键决策提供了机会。结果:为了证明模拟器的能力,我们评估了 HMPL 与传统做法相比对包裹路由和合并策略的影响。初步研究结果表明,HMPL 中节点间的互联增加缩短了转运时间,从而实现了更紧密的客户交付服务。不过,对不同合并启发式方法的研究表明,在固定装运计划下,处理和装运成本之间可能存在权衡,这促使对动态装运服务进行进一步研究。结论:本研究的结果表明,在包裹物流等复杂环境中,不能脱离其他决策孤立地评估创新方法的效益。要对最终结果和基本权衡进行准确评估,需要建立包含所有关键变量的多方面模型。
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Simulation-Based Assessment of Hyperconnected Megacity Parcel Logistics
Background: The concept of Hyperconnected Megacity Parcel Logistics (HMPL) was introduced in 2018 and aims to enhance the efficiency, responsiveness, resilience, and sustainability of parcel movements in megacities. However, evaluating such fundamental solutions presents challenges and requires a comprehensive understanding of all stakeholders and decisions involved. Methods: This study introduces a discrete-event agent-based simulation platform that encompasses critical stakeholders and addresses various levels of decision-making. This platform provides an opportunity to evaluate key decisions within an HMPL structure. Results: To demonstrate the capability of the simulator, we assess the impact of package routing and consolidation strategies facilitated by HMPL compared to traditional practices. Preliminary findings suggest that increased interconnection among nodes in HMPL reduces transit times, thereby enabling tighter customer delivery services. However, examining different consolidation heuristics reveals potential trade-offs between handling and shipping costs under fixed shipment schedules, prompting further investigation into dynamic shipment services. Conclusions: The findings of this study suggest that the benefits of innovative approaches in a complex environment, such as parcel logistics, cannot be evaluated in isolation from other decisions. Accurate assessment of the ultimate outcomes and underlying trade-offs requires multi-faceted models that incorporate all key variables.
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