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Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management

Author

Listed:
  • H. Asefi

    (The University of New South Wales)

  • S. Lim

    (The University of New South Wales)

  • M. Maghrebi

    (The University of New South Wales
    Ferdowsi University of Mashhad)

  • S. Shahparvari

    (RMIT University)

Abstract

Integrated solid waste management (ISWM) comprises activities and processes to collect, transport, treat, recycle and dispose municipal solid wastes. This paper addresses the ISWM location-routing problem in which different types of municipal solid wastes are factored concurrently into an integrated system with all interrelated facilities. To support a cost-effective ISWM system, the number of locations of the system’s components (i.e. transfer stations; recycling, treatment and disposal centres) and truck routing within the system’s components need to be optimized. A mixed-integer linear programming (MILP) model is presented to minimise the total cost of the ISWM system including transportation costs and facility establishment costs. To tackle the non-deterministic polynomial-time hardness of the problem, a stepwise heuristic method is proposed within the frames of two meta-heuristic approaches: (i) variable neighbourhood search (VNS) and (ii) a hybrid VNS and simulated annealing algorithm (VNS + SA). A real-life case study from an existing ISWM system in Tehran, Iran is utilized to apply the proposed model and algorithms. Then the presented MILP model is implemented in CPLEX environment to evaluate the effectiveness of the proposed algorithms for multiple test problems in different scales. The results show that, while both proposed algorithms can effectively solve the problem within practical computing time, the proposed hybrid method efficiently has produced near-optimal solutions with gaps of

Suggested Citation

  • H. Asefi & S. Lim & M. Maghrebi & S. Shahparvari, 2019. "Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management," Annals of Operations Research, Springer, vol. 273(1), pages 75-110, February.
    • Handle: RePEc:spr:annopr:v:273:y:2019:i:1:d:10.1007_s10479-018-2912-1
    DOI: 10.1007/s10479-018-2912-1
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    References listed on IDEAS

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    Cited by:

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    2. Chun-lin Xin & Shuo Liang & Feng-wu Shen, 0. "Reconfiguration of garbage collection system based on Voronoi graph theory: a simulation case of Beijing region," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-21.
    3. Arthur Mahéo & Diego Gabriel Rossit & Philip Kilby, 2023. "Solving the integrated bin allocation and collection routing problem for municipal solid waste: a Benders decomposition approach," Annals of Operations Research, Springer, vol. 322(1), pages 441-465, March.
    4. Ali Ebadi Torkayesh & Hadi Rezaei Vandchali & Erfan Babaee Tirkolaee, 2021. "Multi-Objective Optimization for Healthcare Waste Management Network Design with Sustainability Perspective," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    5. Chunlin Xin & Jie Wang & Ziping Wang & Chia-Huei Wu & Muhammad Nawaz & Sang-Bing Tsai, 2022. "Reverse logistics research of municipal hazardous waste: a literature review," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 1495-1531, February.
    6. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    7. Amin Aghalari & Darweesh Ehssan Salamah & Carlos Marino & Mohammad Marufuzzaman, 2023. "Electric vehicles fast charger location-routing problem under ambient temperature," Annals of Operations Research, Springer, vol. 324(1), pages 721-759, May.
    8. Chun-lin Xin & Shuo Liang & Feng-wu Shen, 2022. "Reconfiguration of garbage collection system based on Voronoi graph theory: a simulation case of Beijing region," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 953-973, July.

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