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A Simulated Annealing Heuristic for the Capacitated Green Vehicle Routing Problem

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  • Nur Mayke Eka Normasari
  • Vincent F. Yu
  • Candra Bachtiyar
  • Sukoyo

Abstract

This research studies the capacitated green vehicle routing problem (CGVRP), which is an extension of the green vehicle routing problem (GVRP), characterized by the purpose of harmonizing environmental and economic costs by implementing effective routes to meet any environmental concerns while fulfilling customer demand. We formulate the mathematical model of the CGVRP and propose a simulated annealing (SA) heuristic for its solution in which the CGVRP is set up as a mixed integer linear program (MILP). The objective of the CGVRP is to minimize the total distance traveled by an alternative fuel vehicle (AFV). This research conducts a numerical experiment and sensitivity analysis. The results of the numerical experiment show that the SA algorithm is capable of obtaining good CGVRP solutions within a reasonable amount of time, and the sensitivity analysis demonstrates that the total distance is dependent on the number of customers and the vehicle driving range.

Suggested Citation

  • Nur Mayke Eka Normasari & Vincent F. Yu & Candra Bachtiyar & Sukoyo, 2019. "A Simulated Annealing Heuristic for the Capacitated Green Vehicle Routing Problem," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-18, January.
    • Handle: RePEc:hin:jnlmpe:2358258
    DOI: 10.1155/2019/2358258
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    Cited by:

    1. Garside, Annisa Kesy & Ahmad, Robiah & Muhtazaruddin, Mohd Nabil Bin, 2024. "A recent review of solution approaches for green vehicle routing problem and its variants," Operations Research Perspectives, Elsevier, vol. 12(C).
    2. Shuo-Yan Chou & Xuan Loc Pham & Thi Anh Tuyet Nguyen & Tiffany Hui-Kuang Yu, 2023. "Optimal maintenance planning with special emphasis on deterioration process and vessel routing for offshore wind systems," Energy & Environment, , vol. 34(4), pages 739-763, June.
    3. Mahmoud Masoud & Mohammed Elhenawy & Shi Qiang Liu & Mohammed Almannaa & Sebastien Glaser & Wael Alhajyaseen, 2023. "A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    4. Vincent F. Yu & Hadi Susanto & Yu-Hsuan Yeh & Shih-Wei Lin & Yu-Tsung Huang, 2022. "The Vehicle Routing Problem with Simultaneous Pickup and Delivery and Parcel Lockers," Mathematics, MDPI, vol. 10(6), pages 1-22, March.
    5. Meng, Shanshan & Guo, Xiuping & Li, Dong & Liu, Guoquan, 2023. "The multi-visit drone routing problem for pickup and delivery services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).

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