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

Distributionally Robust Facility Location with Bimodal Random Demand

In this paper, we consider a decision-maker who wants to determine a subset of locations from a given set of candidate sites to open facilities and accordingly assign customer demand to these open facilities. Unlike classical facility location settings, we focus on a new setting where customer demand is bimodal, i.e., display, or belong to, … Read more

Optimal Residential Users Coordination Via Demand Response: An Exact Distributed Framework

This paper proposes a two-phase optimization framework for users that are involved in demand response programs. In a first phase, responsive users optimize their own household consumption, characterizing not only their appliances and equipment but also their comfort preferences. Subsequently, the aggregator exploits in a second phase this preliminary noncoordinated solution by implementing a coordination … 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

Solving the Time Dependent Minimum Tour Duration and Delivery Man Problems with Dynamic Discretization Discovery

In this paper, we present exact methods for solving the Time Dependent Minimum Duration Problem (TDMTDP) and the Time Dependent Delivery Man Problem (TD-DMP). Both methods are based on a Dynamic Discretization Discovery (DDD) approach for solving the Time Dependent Traveling Salesman Problem with Time Windows (TD-TSPTW). Unlike the TD-TSPTW, the problems we consider in … Read more

Efficient Formulations and Decomposition Approaches for Power Peak Reduction in Railway Traffic via Timetabling

Over the last few years, optimization models for the energy-efficient operation of railway traffic have received more and more attention, particularly in connection with timetable design. In this work, we study the effect of load management via timetabling. The idea is to consider trains as time-flexible consumers in the railway power supply network and to … Read more

Routing and Wavelength Assignment with Protection: A Quadratic Unconstrained Binary Optimization Approach

The routing and wavelength assignment with protection is an important problem in telecommunications. Given an optical network and incoming connection requests, a commonly studied variant of the problem aims to grant maximum number of requests by assigning lightpaths at minimum network resource usage level, while ensuring the provided services remain functional in case of a … Read more

Conference scheduling: a clustering-based approach

Scheduling the technical sessions of scientific events is an arduous task commonly faced by many organizers worldwide. Due the particularities of each conference, there is no consensus regarding the problem definition, and researchers have tackled each specific case individually. Despite their distinct characteristics, one often expects the sessions to be composed of presentations of similar … Read more

Solving AC Optimal Power Flow with Discrete Decisions to Global Optimality

We present a solution framework for general alternating current optimal power flow (AC OPF) problems that include discrete decisions. The latter occur, for instance, in the context of the curtailment of renewables or the switching of power generation units and transmission lines. Our approach delivers globally optimal solutions and is provably convergent. We model AC … Read more

A branch-and-cut algorithm for the Edge Interdiction Clique Problem

Given a graph G and an interdiction budget k, the Edge Interdiction Clique Problem (EICP) asks to find a subset of at most k edges to remove from G so that the size of the maximum clique, in the interdicted graph, is minimized. The EICP belongs to the family of interdiction problems with the aim … Read more