Solving the integrated bin allocation and collection routing problem for municipal solid waste: a Benders decomposition approach

Arthur Mahéo (), Diego Gabriel Rossit () and Philip Kilby ()
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Arthur Mahéo: Monash University, Faculty of IT
Diego Gabriel Rossit: Universidad Nacional del Sur (UNS)-CONICET
Philip Kilby: Australian National University

Annals of Operations Research, 2023, vol. 322, issue 1, No 17, 465 pages

Abstract: Abstract The municipal solid waste system is a complex reverse logistic chain which comprises several optimisation problems. Although these problems are interdependent—i.e., the solution to one of the problems restricts the solution to the other—they are usually solved sequentially in the related literature because each is usually a computationally complex problem. We address two of the tactical planning problems in this chain by means of a Benders decomposition approach: determining the location and/or capacity of garbage accumulation points, and the design and schedule of collection routes for vehicles. Our approach manages to solve medium-sized real-world instances in the city of Bahía Blanca, Argentina, showing smaller computing times than solving a full MIP model.

Keywords: Municipal solid waste; Reverse supply chain; Integrated allocation-routing problem; Benders decomposition algorithm; Valid inequalities; Mixed integer programming (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10479-022-04918-7

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