关于城市物流中移动、存储、取货和交付所使用的主要数学模型的研究:系统回顾

IF 2.3 4区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Systems Pub Date : 2024-09-17 DOI:10.3390/systems12090374
Renan Paula Ramos Moreno, Rui Borges Lopes, José Vasconcelos Ferreira, Ana Luísa Ramos, Diogo Correia
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引用次数: 0

摘要

这篇系统性综述调查了应用于城市物流的主要数学模型,重点是路由、定位和转运问题。这项研究针对的是人口增长和电子商务扩张对高效、可持续物流解决方案日益增长的需求。对 57 篇科学文章进行了全面分析,涵盖了确定性和随机性方法,以及启发式和精确解法。综述显示,启发式方法因其计算效率高而占据主导地位。事实证明,将精确方法与启发式方法相结合,对复杂的物流方案非常有效,既提高了准确性,又提高了效率。同步和中途停留也已成为优化物流运作的关键因素。本综述强调了方法的多样性以及对可持续高效模型的需求。随机模拟的整合仍很有限,这是一个研究空白,随机模型已被证明能提供更稳健的解决方案,解决物流运营中固有的不确定性。这种整合可以提高城市环境中物流解决方案的稳健性和适用性。通过强调当前方法的优势和局限性,它为未来的研究铺平了道路,以便针对城市物流挑战开发更稳健、适应性更强的解决方案,同时强调跨学科合作和使用真实世界数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of the Main Mathematical Models Used in Mobility, Storage, Pickup and Delivery in Urban Logistics: A Systematic Review
This systematic review investigates the main mathematical models applied in urban logistics, focusing on routing, location and transshipment problems. The study addresses the growing demand for efficient and sustainable logistics solutions driven by population growth and the expansion of e-commerce. A thorough analysis of 57 scientific articles was carried out, covering deterministic and stochastic methodologies, as well as heuristic and exact solutions. This review revealed that heuristic methods are predominant due to their computational efficiency. Combining exact methods with heuristics has proven effective for complex logistics scenarios, increasing accuracy and efficiency. Synchronization and intermediate stops have also emerged as critical factors in optimizing logistics operations. This review highlights the diversity of methodologies and the need for sustainable and efficient models. The integration of stochastic simulations remains limited, representing a research gap where stochastic models have been shown to provide more robust solutions in addressing the uncertainties inherent in logistics operations. This integration can increase the robustness and applicability of logistics solutions in urban environments. By highlighting the strengths and limitations of current approaches, it paves the way for future research to develop more robust and adaptable solutions to urban logistics challenges, emphasizing interdisciplinary collaboration and the use of real-world data.
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来源期刊
Systems
Systems Decision Sciences-Information Systems and Management
CiteScore
2.80
自引率
15.80%
发文量
204
审稿时长
11 weeks
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