Robust Vehicle Routing under Uncertainty via Branch-Price-and-Cut

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 … Read more

Estimation of Marginal Cost to Serve Individual Customers

This paper proposes a scenario sampling-based framework to estimate the expected incremental routing cost required so as to incorporate a target customer into an inherently stochastic supply chain network. Inspired from a real-life setting arising in the distribution of industrial gases, we demonstrate our framework and elucidate the quality of the marginal cost estimates it … Read more

On tackling reverse convex constraints for non-overlapping of unequal circles

We study the unequal circle-circle non-overlapping constraints, a form of reverse convex constraints that often arise in optimization models for cutting and packing applications. The feasible region induced by the intersection of circle-circle non-overlapping constraints is highly non-convex, and standard approaches to construct convex relaxations for spatial branch-and-bound global optimization of such models typically yield … Read more

A scenario decomposition algorithm for strategic time window assignment vehicle routing problems

We study the strategic decision-making problem of assigning time windows to customers in the context of vehicle routing applications that are affected by operational uncertainty. This problem, known as the Time Window Assignment Vehicle Routing Problem, can be viewed as a two-stage stochastic optimization problem, where time window assignments constitute first-stage decisions, vehicle routes adhering … Read more