Robust vehicle routing under uncertainty via branch-price-and-cut

Journal Article · Sun Sep 12 00:00:00 EDT 2021 · Optimization and Engineering

DOI:https://doi.org/10.1007/s11081-021-09680-6· OSTI ID:1906188

Wang, Akang ^[1]; Subramanyam, Anirudh ^[2]; Gounaris, Chrysanthos E. ^[1]

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1. Carnegie Mellon University, Pittsburgh, PA (United States)
2. Carnegie Mellon University, Pittsburgh, PA (United States); Argonne National Laboratory (ANL), Lemont, IL (United States)

Here, this paper contemplates how branch-price-and-cut solvers can be employed along with the robust optimization paradigm to address parametric uncertainty in the context of vehicle routing problems. In this setting, given postulated uncertainty sets for customer demands and vehicle travel times, one aims to identify a set of cost-effective routes for vehicles to traverse, such that the vehicle capacities and customer time window constraints are respected under any anticipated demand and travel time realization, respectively. To tackle such problems, we propose a novel approach that combines cutting-plane techniques with an advanced branch-price-and-cut algorithm. Specifically, we use deterministic pricing procedures to generate "partially robust" vehicle routes and then utilize robust versions of rounded capacity inequalities and infeasible path elimination constraints to guarantee complete robust feasibility of routing designs against demand and travel time uncertainty. In contrast to recent approaches that modify the pricing algorithm, our approach is both modular and versatile. It permits the use of advanced branch-price-and-cut technologies without significant modification, while it can admit a variety of uncertainty sets that are commonly used in robust optimization but could not be previously employed in a branch-price-and-cut setting.

• Research Organization: Argonne National Laboratory (ANL), Lemont, IL (United States)
• Sponsoring Organization: Carnegie Mellon University; USDOE
• Grant/Contract Number: AC02-06CH11357
• OSTI ID: 1906188
• Journal Information: Optimization and Engineering, Journal Name: Optimization and Engineering Journal Issue: 4 Vol. 23; ISSN 1389-4420
• Publisher: Springer
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
branch-price-and-cut
demand uncertainty
infeasible path elimination constraints
robust optimization
robust rounded capacity inequalities
travel time uncertainty
vehicle routing