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Effective and efficient: large-scale dynamic city express

Published: 03 November 2015 Publication History
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  • Abstract

    City express services are in great demand in recent years. However, the current city express system is found to be unsatisfactory for both the service providers and customers. In this paper, we are the first to systematically study the large-scale dynamic city express problem. We aim to increase both the effectiveness and the efficiency of the scheduling algorithm. To improve the effectiveness, we adopt a batch assignment strategy that computes the pickup-delivery routes for a group of requests received in a short period rather than dealing with each request individually. To improve the efficiency, we design a two-level priority queue structure to reduce redundant shortest distance calculation and repeated candidate generation. We develop a simulation system and conduct extensive performance studies in the real road network of Beijing city. The experimental results demonstrate the high effectiveness and efficiency of our algorithm.

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    Cited By

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    • (2024)A Dynamic Redeployment System for Mobile Ambulances in Qatar, Empowered by Deep Reinforcement Learning2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592430(980-985)Online publication date: 27-May-2024
    • (2019)Representing Urban FormsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.283702731:3(535-548)Online publication date: 1-Mar-2019
    • (2016)Self-adaptation of multi-agent systems in dynamic environments based on experience exchangesJournal of Systems and Software10.1016/j.jss.2016.09.025122:C(165-179)Online publication date: 1-Dec-2016

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    Published In

    cover image ACM Conferences
    SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems
    November 2015
    646 pages
    ISBN:9781450339674
    DOI:10.1145/2820783
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 03 November 2015

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    Author Tags

    1. batch assignment
    2. city express service
    3. logistics

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    SIGSPATIAL '15 Paper Acceptance Rate 38 of 212 submissions, 18%;
    Overall Acceptance Rate 220 of 1,116 submissions, 20%

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    • (2024)A Dynamic Redeployment System for Mobile Ambulances in Qatar, Empowered by Deep Reinforcement Learning2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592430(980-985)Online publication date: 27-May-2024
    • (2019)Representing Urban FormsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.283702731:3(535-548)Online publication date: 1-Mar-2019
    • (2016)Self-adaptation of multi-agent systems in dynamic environments based on experience exchangesJournal of Systems and Software10.1016/j.jss.2016.09.025122:C(165-179)Online publication date: 1-Dec-2016

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