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

Asefi, H, Lim, S, Maghrebi, M and Shahparvari, S 2019, 'Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management', Annals of Operations Research, vol. 273, no. 12, pp. 75-110.


Document type: Journal Article
Collection: Journal Articles

Title Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management
Author(s) Asefi, H
Lim, S
Maghrebi, M
Shahparvari, S
Year 2019
Journal name Annals of Operations Research
Volume number 273
Issue number 12
Start page 75
End page 110
Total pages 36
Publisher Springer
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 < 4%, compared to the exact results. In comparison with the current cost of the existing ISWM system in the study area, the presented MILP model and proposed heuristic methods effectively reduce the total costs by 20-22%.
Subject Logistics and Supply Chain Management
Keyword(s) Integrated solid waste management
Location-routing problem
Mixed-integer linear programming
Municipal solid waste
Simulated annealing
Variable neighbourhood search
DOI - identifier 10.1007/s10479-018-2912-1
Copyright notice © Springer Science+Business Media, LLC, part of Springer Nature 2018
ISSN 0254-5330
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