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An ant colony system for responsive dynamic vehicle routing

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  • Schyns, M.

Abstract

We present an algorithm based on an ant colony system to deal with a broad range of Dynamic Capacitated Vehicle Routing Problems with Time Windows, (partial) Split Delivery and Heterogeneous fleets (DVRPTWSD). We address the important case of responsiveness. Responsiveness is defined here as completing a delivery as soon as possible, within the time window, such that the client or the vehicle may restart its activities. We develop an interactive solution to allow dispatchers to take new information into account in real-time. The algorithm and its parametrization were tested on real and artificial instances. We first illustrate our approach with a problem submitted by Liege Airport, the 8th biggest cargo airport in Europe. The goal is to develop a decision system to optimize the journey of the refueling trucks. We then consider some classical VRP benchmarks with extensions to the responsiveness context.

Suggested Citation

  • Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    • Handle: RePEc:eee:ejores:v:245:y:2015:i:3:p:704-718
    DOI: 10.1016/j.ejor.2015.04.009
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    3. Aderemi Oluyinka Adewumi & Olawale Joshua Adeleke, 2018. "A survey of recent advances in vehicle routing problems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 155-172, February.
    4. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
    5. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02879681, HAL.
    6. Cong Wang & Zhongxiu Peng & Xijun Xu, 2021. "A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies," Mathematics, MDPI, vol. 9(18), pages 1-34, September.
    7. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency relief routing models for injured victims considering equity and priority," Annals of Operations Research, Springer, vol. 283(1), pages 1573-1606, December.
    8. Moosavi, Amirhossein & Ozturk, Onur & Patrick, Jonathan, 2022. "Staff scheduling for residential care under pandemic conditions: The case of COVID-19," Omega, Elsevier, vol. 112(C).
    9. Han, Xue & Zhao, Peixin & Kong, Dexin, 2023. "Two-stage optimization of airport ferry service delay considering flight uncertainty," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1103-1116.
    10. Farzaneh Karami & Wim Vancroonenburg & Greet Vanden Berghe, 2020. "A periodic optimization approach to dynamic pickup and delivery problems with time windows," Journal of Scheduling, Springer, vol. 23(6), pages 711-731, December.
    11. Nikola Mardešić & Tomislav Erdelić & Tonči Carić & Marko Đurasević, 2023. "Review of Stochastic Dynamic Vehicle Routing in the Evolving Urban Logistics Environment," Mathematics, MDPI, vol. 12(1), pages 1-44, December.
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    14. Li Ma & Minghan Xin & Yi-Jia Wang & Yanjiao Zhang, 2022. "Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services," Mathematics, MDPI, vol. 10(21), pages 1-22, October.

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