Optimal Steiner Trees Under Node and Edge Privacy Conflicts

In this work, we suggest concepts and solution methodologies for a series of strategic network design problems that find application in highly data-sensitive industries, such as, for instance, the high-tech, governmental, or military sector. Our focus is on the installation of widely used cost-efficient tree-structured communication infrastructure. As base model we use the well-known Steiner … Read more

Improved Branch-and-Cut for the Inventory Routing Problem Based on a Two-Commodity Flow Formulation

This paper examines the Inventory Routing Problem (IRP) with Maximum Level inventory policy. The IRP is a broad class of hard to solve problems with numerous practical applications in the field of freight transportation and logistics. A supplier is responsible for determining the timing and the quantity of replenishment services offered to a set of … Read more

Short-Term Inventory-Aware Equipment Management in Service Networks

Logistics companies often operate a heterogeneous fleet of equipment to support their service network operations. This introduces a layer of planning complexity as facilities need to maintain appropriate levels of equipment types to support operations throughout the planning horizon. We formulate an optimization model that minimizes the cost of executing a load plan, assuming knowledge … Read more

Bicriteria approaches for an optimal balance between resilience and cost-effectiveness of supply chains

In supply chain optimization multiple objectives are considered simultaneously, for example to increase resilience and reduce costs. In this paper we discuss the corresponding bicriteria problems to find a good balance between these two objectives. We give a general model for supply chain resilience that integrates strategic decisions with the operational level. This modular model … Read more

A Branch-Cut-and-Price Algorithm for the Time-Dependent Electric Vehicle Routing Problem with Time Windows

The adoption of electric vehicles (EVs) within last-mile deliveries is considered one of the key transformations towards more sustainable logistics. The inclusion of EVs introduces new operational constraints to the models such as a restricted driving range and the possibility to perform recharges in-route. The discharge of the typical batteries is complex and depends on … Read more

Adaptable Energy Management System for Smart Buildings

This paper presents a novel adaptable energy management system for smart buildings. In this framework we model the energy consumption of a living unit, and its energy exchange with the surroundings. We explicitly consider the impact of the outside environment and design features such as building orientation, automatic shading, and double facade. We formulate this … Read more

Decomposition and Adaptive Sampling for Data-Driven Inverse Linear Optimization

This work addresses inverse linear optimization where the goal is to infer the unknown cost vector of a linear program. Specifically, we consider the data-driven setting in which the available data are noisy observations of optimal solutions that correspond to different instances of the linear program. We introduce a new formulation of the problem that, … Read more

A Unified Approach to Solve Convex Hull Pricing and Average Incremental Cost Pricing

This paper introduces a unified approach to solving convex hull pricing (CHP) and average incremental cost (AIC) pricing problems. By developing a convex hull and convex envelope formulation for individual resources, a CHP model that minimizes uplift can be solved by linear programming (LP) using relaxation of the binary terms of the security constrained unit … Read more

A Column Generation Based Heuristic for the Split Delivery Vehicle Routing Problem with Time Windows

The vehicle routing problem with time windows (VRPTW) is one of the most studied variants of routing problems. We consider the Split Delivery VRPTW (SDVRPTW), an extension in which customers can be visited multiple times, if advantageous. While this additional flexibility can result in significant cost reductions, it also results in additional modeling and computational … Read more

Randomized Assortment Optimization

When a firm selects an assortment of products to offer to customers, it uses a choice model to anticipate their probability of purchasing each product. In practice, the estimation of these models is subject to statistical errors, which may lead to significantly suboptimal assortment decisions. Recent work has addressed this issue using robust optimization, where … Read more