DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods

In this paper, we propose an innovative variable fixing strategy called deep Lagrangian underestimate fixing (DeLuxing). It is a highly effective approach for removing unnecessary variables in column-generation (CG)-based exact methods used to solve challenging discrete optimization problems commonly encountered in various industries, including vehicle routing problems (VRPs). DeLuxing employs a novel linear programming (LP) … Read more

Optimal Multi-Agent Pickup and Delivery Using Branch-and-Cut-and-Price

Given a set of agents and a set of pickup-delivery requests located on a two-dimensional map, the Multi-Agent Pickup and Delivery problem assigns the requests to the agents such that every agent moves from its start location to the locations of its assigned requests and finally to its end location without colliding into any other … Read more

Delay-Resistant Robust Vehicle Routing with Heterogeneous Time Windows

We consider a robust variant of the vehicle routing problem with heterogeneous time windows (RVRP-HTW) with a focus on delay-resistant solutions. Here, customers have different availability time windows for every vehicle and must be provided with a preferably tight appointment window for the planned service. Different vehicles are a possibility to model different days on … Read more

Planning a Zero-Emission Mixed-Fleet Public Bus System with Minimal Life Cycle Cost

The variety of available technology options for the operation of zero-emission bus systems gives rise to the problem of finding an optimal technology decision for bus operators. Among others, overnight charging, opportunity charging and hydrogen-based technology options are frequently pursued technological solutions. As their operating conditions are strongly influenced by the urban context, an optimal … Read more

Inverse Optimization for Routing Problems

We propose a method for learning decision-makers’ behavior in routing problems using Inverse Optimization (IO). The IO framework falls into the supervised learning category and builds on the premise that the target behavior is an optimizer of an unknown cost function. This cost function is to be learned through historical data, and in the context … Read more

Robust Workforce Management with Crowdsourced Delivery

We investigate how crowdsourced delivery platforms with both contracted and ad-hoc couriers can effectively manage their workforce to meet delivery demands amidst uncertainties. Our objective is to minimize the hiring costs of contracted couriers and the crowdsourcing costs of ad-hoc couriers while considering the uncertain availability and behavior of the latter. Due to the complication … Read more

Optimization-based Learning for Dynamic Load Planning in Trucking Service Networks

Citation Ojha, R., Chen, W., Zhang, H., Khir, R., Erera, A. & Van Hentenryck, P. (2023). Optimization-based Learning for Dynamic Load Planning in Trucking Service Networks. Article Download View Optimization-based Learning for Dynamic Load Planning in Trucking Service Networks

Integrating Order-to-Delivery Time Sensitivity in E-Commerce Middle-Mile Consolidation Network Design

This paper proposes an approach that leverages data on customer purchasing sensitivity to quoted order-to-delivery times (ODTs) when designing middle-mile consolidation networks to maximize the profit of e-commerce retailers. Our approach integrates quoted ODT-dependent sales volume predictions into a new mixed-integer program (MIP) that simultaneously determines ODT quotes and a consolidation plan, characterized by the … Read more

The Vehicle Routing Problem with Access Restrictions

To mitigate the negative effect of freight vehicles on urban areas, many cities have implemented road accessibility restrictions, including limited traffic zones, which restrict access to specific areas during certain times of the day. Implementing these zones creates a trade-off between the delivery cost and time, even under the assumption of equal traversal time and … Read more

A new upper bound of the Euclidean TSP constant

Let X1, X2, . . . , Xn be n independent and uniformly distributed random points in a compact region R ⊂ R2 of area 1. Let TSP(X1,…,Xn) denote the length of the optimal Euclidean traveling salesman tour that traverses all these points. The classical Beardwood-Halton-Hammersley theorem (1959) proved the existence of a universal constant … Read more