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Recyclables Collection Route Balancing Problem with Heterogeneous Fleet

Author

Listed:
  • Roger Książek

    (Faculty of Management, AGH University of Science and Technology, 30-059 Krakow, Poland
    These authors contributed equally to this work.)

  • Katarzyna Gdowska

    (Faculty of Management, AGH University of Science and Technology, 30-059 Krakow, Poland
    These authors contributed equally to this work.)

  • Antoni Korcyl

    (Faculty of Management, AGH University of Science and Technology, 30-059 Krakow, Poland
    These authors contributed equally to this work.)

Abstract

Nowadays, robust and efficient solid waste collection is crucial to motivate citizens to participate in the circular economy by sorting recyclable solid waste. Vocational vehicles, including garbage trucks, contribute significantly to CO 2 emissions; therefore, it is strongly recommended, and in the European Union it is mandatory, to replace conventional-fuel-based garbage trucks with electric ones. For providing sustainable and energy-efficient solid waste collection with a heterogeneous fleet, in-depth mathematical computations are needed to support solving complex decision-making problems, including crew rostering and vehicle routing, because the distance and capacity of electric garbage trucks differ from conventional-fuel-based ones. However, the literature on solid waste collection using electric garbage trucks is still relatively scarce. The main contribution of this paper is developing an optimization problem for balancing travel distance assigned to each garbage truck of a heterogeneous fleet. The problem is based on specific requirements of the Municipal Solid Waste Management in Cracow, Poland, where the working time of routes is balanced and the total time of collection service can be minimized. For the problem, an MIP program was developed to generate optimal crew schedules, so that the hitherto network of segregated solid waste pickup nodes can be served using a heterogeneous fleet in which the share of electric garbage trucks is up to 30%. We study the impact of the changed composition of the fleet on modifications in crew rostering due to the shorter range of an electric vehicle compared to a conventional-fuel-based one.

Suggested Citation

  • Roger Książek & Katarzyna Gdowska & Antoni Korcyl, 2021. "Recyclables Collection Route Balancing Problem with Heterogeneous Fleet," Energies, MDPI, vol. 14(21), pages 1-16, November.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7406-:d:673762
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    References listed on IDEAS

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    1. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    2. Meryem Berghida & Abdelmadjid Boukra, 2016. "Quantum Inspired Algorithm for a VRP with Heterogeneous Fleet Mixed Backhauls and Time Windows," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 7(4), pages 18-38, October.
    3. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    4. Hossein Asefi & Shahrooz Shahparvari & Prem Chhetri, 2020. "Advances in sustainable integrated solid waste management systems: lessons learned over the decade 2007–2018," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(13), pages 2287-2312, November.
    5. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Panagiotis-Petros Matthopoulos & Stella Sofianopoulou, 2019. "A firefly algorithm for the heterogeneous fixed fleet vehicle routing problem," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 33(2), pages 204-224.
    7. Anna Skowrońska-Szmer & Anna Kowalska-Pyzalska, 2021. "Key Factors of Development of Electromobility AMONG Microentrepreneurs: A Case Study from Poland," Energies, MDPI, vol. 14(3), pages 1-25, February.
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