Journal ArticleDOI
Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions
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TLDR
Wang et al. as discussed by the authors proposed an effective large-scale mobile crowd-tasking model in which a large pool of citizen workers are used to perform the last-mile delivery, and formulated it as a network min-cost flow problem and proposed various pruning techniques that can dramatically reduce the network size.Abstract:
In urban logistics, the last-mile delivery from the warehouse to the consumer’s home has become more and more challenging with the continuous growth of E-commerce. It requires elaborate planning and scheduling to minimize the global traveling cost, but often results in unattended delivery as most consumers are away from home. In this paper, we propose an effective large-scale mobile crowd-tasking model in which a large pool of citizen workers are used to perform the last-mile delivery. To efficiently solve the model, we formulate it as a network min-cost flow problem and propose various pruning techniques that can dramatically reduce the network size. Comprehensive experiments were conducted with Singapore and Beijing datasets. The results show that our solution can support real-time delivery optimization in the large-scale mobile crowd-sourcing problem.read more
Citations
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A review of last mile logistics innovations in an externalities cost reduction vision
TL;DR: A review of the recent scientific literature contributions on innovative strategies for last-mile logistics, focusing on externalities cost reduction, is presented in this paper, which is consistent with a general formulation proposed to evaluate external costs in urban area.
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Crowd logistics: an opportunity for more sustainable urban freight transport?
TL;DR: In this article, the authors developed a suitable and comprehensive definition for crowd logistics and identified which factors determine the sustainability potential of CL and indicated whether the identified characteristics affect the economy, society and/or environment.
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Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models
TL;DR: In this paper, the authors provide a comprehensive review on LML models in the modern e-commerce context, and propose four future research areas reflecting likely digital supply chain evolutions.
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A survey of models and algorithms for optimizing shared mobility
TL;DR: This survey sets out to review recent research in this area, including different optimization approaches, and to provide guidelines and promising directions for future research, making a distinction between prearranged and real-time problem settings and their methods of solution.
Journal ArticleDOI
Last-mile delivery concepts: a survey from an operational research perspective
TL;DR: This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept, and systematically record the alternative delivery concepts in a compact notation scheme.
References
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Book
Network Flows: Theory, Algorithms, and Applications
TL;DR: In-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models are presented.
Journal ArticleDOI
The Truck Dispatching Problem
George B. Dantzig,J. H. Ramser +1 more
TL;DR: A procedure based on a linear programming formulation is given for obtaining a near optimal solution to the optimum routing of a fleet of gasoline delivery trucks between a bulk terminal and a large number of service stations supplied by the terminal.
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Mining interesting locations and travel sequences from GPS trajectories
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Proceedings ArticleDOI
GeoCrowd: enabling query answering with spatial crowdsourcing
Leyla Kazemi,Cyrus Shahabi +1 more
TL;DR: This paper introduces a taxonomy for spatial crowdsourcing, and focuses on one class of this taxonomy, in which workers send their locations to a centralized server and thereafter the server assigns to every worker his nearby tasks with the objective of maximizing the overall number of assigned tasks.
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