A primal heuristic to compute an upper bound set for multi-objective 0-1 linear optimisation problems

This paper presents an algorithm aiming to compute an upper bound set for a multi-objective linear optimisation problem with binary variables (p-01LP). Inspired by the well known « Feasibility Pump » algorithm in single objective optimisation, it belongs to the class of primal heuristics. The proposed algorithm, named « Gravity Machine », aims to deal … Read more

Generating Cutting Inequalities Successively for Quadratic Optimization Problems in Binary Variables

We propose a successive generation of cutting inequalities for binary quadratic optimization problems. Multiple cutting inequalities are successively generated for the convex hull of the set of the optimal solutions $\subset \{0, 1\}^n$, while the standard cutting inequalities are used for the convex hull of the feasible region. An arbitrary linear inequality with integer coefficients … Read more

A Joint Demand and Supply Management Approach to Large Scale Urban Evacuation Planning: Evacuate or Shelter-in-Place, Staging and Dynamic Resource Allocation

Urban evacuation management is challenging to implement as it requires planning and coordination over a large geographical area. To address these challenges and to bolster evacuation planning and management, joint supply and demand management strategies should be considered. In this study, we explore and jointly optimize evacuate or shelter-in-place, dynamic resource allocation, and staging decisions … Read more

High-Rank Matrix Completion by Integer Programming

In the High-Rank Matrix Completion (HRMC) problem, we are given a collection of n data points, arranged into columns of a matrix X, and each of the data points is observed only on a subset of its coordinates. The data points are assumed to be concentrated near a union of low-dimensional subspaces. The goal of … Read more

Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) problem with Uncertainties

The Home Service Assignment, Routing, and Appointment scheduling (H-SARA) problem integrates the strategical fleet-sizing, tactical assignment, operational vehicle routing and scheduling subproblems at different decision levels, with a single period planning horizon and uncertainty (stochasticity) from the service duration, travel time, and customer cancellation rate. We propose a two-stage stochastic mixed-integer linear programming model for … Read more

Integrated Vehicle Routing and Service Scheduling under Time and Cancellation Uncertainties with Application in Non-Emergency Medical Transportation

In this paper, we consider an integrated vehicle routing and service scheduling problem for serving customers in distributed locations who need pick-up, drop-off or delivery services. We take into account the random trip time, non-negligible service time and possible customer cancellations, under which an ill-designed schedule may lead to undesirable vehicle idleness and customer waiting. … Read more

A Penalty Branch-and-Bound Method for Mixed-Binary Linear Complementarity Problems

Linear complementarity problems (LCPs) are an important modeling tool for many practically relevant situations but also have many important applications in mathematics itself. Although the continuous version of the problem is extremely well studied, much less is known about mixed-integer LCPs (MILCPs) in which some variables have to be integer-valued in a solution. In particular, … Read more

Designing an optimal sequence of non-pharmaceutical interventions for controlling COVID-19

The COVID-19 pandemic has had an unprecedented impact on global health and the economy since its inception in December, 2019 in Wuhan, China. Non-pharmaceutical interventions (NPI) like lockdowns and curfews have been deployed by affected countries for controlling the spread of infections. In this paper, we develop a Mixed Integer Non-Linear Programming (MINLP) epidemic model … Read more

Exact Logit-Based Product Design

The share-of-choice product design (SOCPD) problem is to find the product, as defined by its attributes, that maximizes market share arising from a collection of customer types or segments. When customers follow a logit model of choice, the market share is given by a weighted sum of logistic probabilities, leading to the logit-based share-of-choice product … Read more

SDP-quality bounds via convex quadratic relaxations for global optimization of mixed-integer quadratic programs

We consider the global optimization of nonconvex mixed-integer quadratic programs with linear equality constraints. In particular, we present a new class of convex quadratic relaxations which are derived via quadratic cuts. To construct these quadratic cuts, we solve a separation problem involving a linear matrix inequality with a special structure that allows the use of … Read more