A robust optimization approach for the vehicle routing problem with selective backhauls

Maria João Santos, Eduardo Curcio, Mauro Henrique Mulati, Pedro Amorim and Flávio Keidi Miyazawa

Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 136, issue C

Abstract: The Vehicle Routing Problem with Selective Backhauls (VRPSB) aims to minimize the total routing costs minus the total revenue collected at backhaul customers. We explore a VRPSB under uncertain revenues. A deterministic VRPSB is formulated as a mixed-integer programming problem and two robust counterparts are derived. A novel method to estimate the probabilistic bounds of constraint violation is designed. A robust metaheuristic is developed, requiring little time to obtain feasible solutions with average gap of 1.40%. The robust approach studied demonstrates high potential to tackle the problem, requiring similar computing effort and maintaining the same tractability as the deterministic modeling.

Keywords: Vehicle routing problem with selective backhauls; Robust optimization; Branch-and-cut; Adaptive large neighborhood search (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.tre.2020.101888

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