Thibaut Vidal

Thibaut Vidal
Polytechnique Montréal · Department of Mathematics and Industrial Engineering

PhD

About

93
Publications
58,572
Reads
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3,869
Citations
Education
September 2009 - December 2012
Université de Montréal
Field of study
  • Computer Science and Operations Research
September 2008 - September 2009
University Joseph Fourier - Grenoble 1
Field of study
  • Computer Science & Operations Research
September 2006 - September 2009

Publications

Publications (93)
Preprint
An equitable distribution of workload is essential when deploying vehicle routing solutions in practice. For this reason, previous studies have formulated vehicle routing problems with workload-balance objectives or constraints, leading to trade-off solutions between routing costs and workload equity. These methods consider a single planning period...
Preprint
Decision diagrams for classification have some notable advantages over decision trees, as their internal connections can be determined at training time and their width is not bound to grow exponentially with their depth. Accordingly, decision diagrams are usually less prone to data fragmentation in internal nodes. However, the inherent complexity o...
Preprint
Counterfactual explanations describe how to modify a feature vector in order to flip the outcome of a trained classifier. Several heuristic and optimal methods have been proposed to generate these explanations. However, the robustness of counterfactual explanations when the classifier is re-trained has yet to be studied. Our goal is to obtain count...
Article
Full-text available
Pairwise relational information is a useful way of providing partial supervision in domains where class labels are difficult to acquire. This work presents a clustering model that incorporates pairwise annotations in the form of must-link and cannot-link relations and considers possible annotation inaccuracies (i.e., a common setting when experts p...
Preprint
Full-text available
We consider the vehicle routing problem with stochastic demands (VRPSD), a problem in which customer demands are known in distribution at the route planning stage and revealed during route execution upon arrival at each customer. A long-standing open question on the VRPSD concerns the benefits of allowing, during route execution, partial reordering...
Article
Full-text available
The last decades have seen a tremendous amount of research being devoted to effectively managing vehicle fleets and minimizing empty mileage. However, in contrast to, e.g., the air transport sector, the question of how to best assign crews to vehicles, has received very little attention in the road transport sector. The vast majority of road freigh...
Article
Full-text available
The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest. Yet, despite extensive methodological progress, many recent studies are hampered by the limited access to simple and efficient open-source solution methods. Given the sophistication of current algori...
Preprint
Some of today's greatest challenges in urban environments concern individual mobility and rapid parcel delivery. Given the surge of e-commerce and the ever-increasing volume of goods to be delivered, we explore possible logistic solutions by proposing algorithms to add parcel-transport services to ride-hailing systems. Toward this end, we present a...
Preprint
Neighborhood search is a cornerstone of state-of-the-art traveling salesman and vehicle routing metaheuristics. While neighborhood exploration procedures are well developed for problems with individual services, their counterparts for one-to-one pickup-and-delivery problems have been more scarcely studied. A direct extension of classic neighborhood...
Preprint
Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions. The absence of guarantees of performance and robustness hinders trustworthiness. In this paper, we take a disciplined approach towards counterfactual explanations for tree ensembles. We advocate for a model-based search aiming...
Preprint
The rise of battery-powered vehicles for mobility-on-demand leads to many technical and methodological hurdles. Among these, the efficient planning of a shared electric fleet to fulfill passenger transportation requests still represents a major challenge. This is due to the specific constraints of electric vehicles, bound by their autonomy and nece...
Preprint
Pairwise relational information is a useful way of providing partial supervision in domains where class labels are difficult to acquire. This work presents a clustering model that incorporates pairwise annotations in the form of must-link and cannot-link relations and considers possible annotation inaccuracies (i.e., a common setting when experts p...
Article
Full-text available
Vehicle routing algorithms usually reformulate the road network into a complete graph in which each arc represents the shortest path between two locations. Studies on time-dependent routing followed this model and therefore defined the speed functions on the complete graph. We argue that this model is often inadequate, in particular for arc routing...
Article
Full-text available
We introduce pattern injection local search (PILS), an optimization strategy that uses pattern mining to explore high-order local-search neighborhoods, and illustrate its application on the vehicle routing problem. PILS operates by storing a limited number of frequent patterns from elite solutions. During the local search, each pattern is used to d...
Preprint
The Degree-Corrected Stochastic Block Model (DCSBM) is a popular model to generate random graphs with community structure given an expected degree sequence. The standard approach of community detection based on the DCSBM is to search for the model parameters that are the most likely to have produced the observed network data through maximum likelih...
Preprint
The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest. Yet, despite extensive methodological progress, many recent studies are hampered by the limited access to simple and efficient open-source solution methods. Given the sophistication of current algori...
Article
The job Sequencing and tool Switching Problem (SSP) has been extensively studied in the field of operations research, due to its practical relevance and methodological interest. Given a machine that can load a limited amount of tools simultaneously and a number of jobs that require a subset of the available tools, the SSP seeks a job sequence that...
Conference Paper
Full-text available
The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix possible sources of mistakes and biases. Tree ensembles, in particular, offer a good prediction quality in various d...
Article
In this paper, we are interested in the exact solution of the vehicle routing problem with backhauls (VRPB), a classical vehicle routing variant with two types of customers: linehaul (delivery) and backhaul (pickup) ones. We propose two branch-cut-and-price (BCP) algorithms for the VRPB. The first one follows the traditional approach with one prici...
Preprint
Vehicle routing algorithms usually reformulate the road network into a complete graph in which each arc represents the shortest path between two locations. Studies on time-dependent routing followed this model and therefore defined the speed functions on the complete graph. We argue that this model is often inadequate, in particular for arc routing...
Preprint
Full-text available
Stochastic block models (SBMs) are often used to find assortative community structures in networks, such that the probability of connections within communities is higher than in between communities. However, classic SBMs are not limited to assortative structures. In this study, we discuss the implications of this model-inherent indifference towards...
Article
Full-text available
Efficiency and security are the two major concerns in cash-in-transit transportation planning. Whereas efficiency is generally achieved by finding short routes, security can be improved by generating dissimilar visit patterns. To achieve a good balance between these two objectives, the vehicle routing problem with arrival time diversification (VRPA...
Preprint
The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix possible sources of mistakes and biases. Tree ensembles offer a good prediction quality in various domains, but the...
Preprint
Full-text available
We introduce pattern injection local search (PILS), an optimization strategy that uses pattern mining to explore high-order local-search neighborhoods, and illustrate its application on the vehicle routing problem. PILS operates by storing a limited number of frequent patterns from elite solutions. During the local search, each pattern is used to d...
Article
Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristic...
Preprint
Full-text available
The job sequencing and tool switching problem (SSP) has been extensively studied in the field of operations research, due to its practical relevance and methodological interest. Given a machine that can load a limited amount of tools simultaneously and a number of jobs that require a subset of the available tools, the SSP seeks a job sequence that...
Article
Full-text available
Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging pro...
Article
Full-text available
This paper introduces a bi-objective model for the offshore supply vessel planning problem (SVPP) in the oil & gas industry. The SVPP consists of determining a new weekly plan for sailing the platform supply vessels whenever the sailing plan needs revising due to some major events, such as the arrival or removal of drilling rigs, and demand increas...
Preprint
Full-text available
Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a brief survey of existing and emerging problem...
Preprint
Full-text available
Hashiwokakero, or simply Hashi, is a Japanese single-player puzzle played on a rectangular grid with no standard size. Some cells of the grid contain a circle, called island, with a number inside it ranging from one to eight. The remaining positions of the grid are empty. The player must connect all of the islands by drawing a series of horizontal...
Article
Full-text available
We investigate how to partition a rectangular region of length L1 and height L2 into n rectangles of given areas (a1,⋯,an) using two-stage guillotine cuts, so as to minimize either (i) the sum of the perimeters, (ii) the largest perimeter, or (iii) the maximum aspect ratio of the rectangles. These problems play an important role in the ongoing Viet...
Article
Full-text available
Minimum sum-of-squares clustering (MSSC) is a widely used clustering model, of which the popular K-means algorithm constitutes a local minimizer. It is well known that the solutions of K-means can be arbitrarily distant from the true MSSC global optimum, and dozens of alternative heuristics have been proposed for this problem. However, no other alg...
Article
Full-text available
We consider a family of rich vehicle routing problems (RVRP) which have the particularity to combine a heterogeneous fleet with other attributes, such as backhauls, multiple depots, split deliveries, site dependency, open routes, duration limits, and time windows. To efficiently solve these problems, we propose a hybrid metaheuristic which combines...
Article
Full-text available
After decades of intensive research on the vehicle routing problem (VRP), many highly efficient single‐objective heuristics exist for a multitude of VRP variants. But when new side‐objectives emerge—such as service quality, workload balance, pollution reduction, consistency—the prevailing approach has been to develop new, problem‐specific, and incr...
Preprint
In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections, ship-dependent starting locations, travel times and costs, time windows, incompatibility constraints, among other features. Together, these characteristics...
Article
Full-text available
The partial digest problem consists in retrieving the positions of a set of points on the real line from their unlabeled pairwise distances. This problem is critical for DNA sequencing, as well as for phase retrieval in X-ray crystallography. When some of the distances are missing, this problem generalizes into a “minimum distance superset problem”...
Article
Full-text available
We propose an iterated local search based on several classes of local and large neighborhoods for the bin packing problem with conflicts. This problem, which combines the characteristics of both bin packing and vertex coloring, arises in various application contexts such as logistics and transportation, timetabling, and resource allocation for clou...
Article
Full-text available
A minimum dominating set in a graph is a minimum set of vertices such that every vertex of the graph either belongs to it, or is adjacent to one vertex of this set. This mathematical object is of high relevance in a number of applications related to social networks analysis, design of wireless networks, coding theory, and data mining, among many ot...
Article
Full-text available
We introduce an electric vehicle routing problem combining conventional, plug-in hybrid, and electric vehicles. Electric vehicles are constrained in their service range by their battery capacity, and may require time-consuming recharging operations at some specific locations. Plug-in hybrid vehicles have two engines, an internal combustion engine a...
Preprint
Full-text available
We investigate how to partition a rectangular region of length $L_1$ and height $L_2$ into $n$ rectangles of given areas $(a_1, \dots, a_n)$ using two-stage guillotine cuts, so as to minimize either (i) the sum of the perimeters, (ii) the largest perimeter, or (iii) the maximum aspect ratio of the rectangles. These problems play an important role i...
Preprint
Full-text available
Minimum sum-of-squares clustering (MSSC) is a widely used clustering model, of which the popular K-means algorithm constitutes a local minimizer. It is well known that the solutions of K-means can be arbitrarily distant from the true MSSC global optimum, and dozens of alternative heuristics have been proposed for this problem. However, no other alg...
Article
Full-text available
We investigate a structural decomposition for the capacitated vehicle routing problem (CVRP) based on vehicle-to-customer "assignment" and visits "sequencing" decision variables. We show that an heuristic search focused on assignment decisions with a systematic optimal choice of sequences (using Concorde TSP solver) during each move evaluation is p...
Article
The capacitated p-center problem requires to select p facilities from a set of candidates to service a number of customers, subject to facility capacity constraints, with the aim of minimizing the maximum distance between a customer and its associated facility. The problem is well known in the field of facility location, because of the many applica...
Article
Two-echelon distribution systems are attractive from an economical standpoint and help keeping large vehicles out of city centers. Large trucks can be used to deliver goods to intermediate facilities in accessible locations, whereas smaller vehicles allow to reach the final customers. Due to their reduced size and emissions, companies have adopted...
Article
Full-text available
In practical vehicle routing problems (VRPs), important non-monetary benefits can be achieved with more balanced operational plans which explicitly consider workload equity. This has motivated practitioners to include a wide variety of balancing criteria in decision support systems, and researchers to examine the properties of these criteria and th...
Article
Full-text available
We consider a family of Rich Vehicle Routing Problems (RVRP) which have the particularity to combine a heterogeneous fleet with other attributes, such as backhauls, multiple depots, split deliveries, site dependency, open routes, duration limits, and time windows. To efficiently solve these problems, we propose a hybrid metaheuristic which combines...
Article
We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, "pickups and deli...
Conference Paper
Vehicle Routing Problems (VRP) involve designing least-cost delivery routes to visit a geographically-dispersed set of customers. Over the past 60 years, this class of problems has been the subject of considerable work, summing up to thousands of articles. In 2017, we can reasonably say that the classical capacitated VRP (with only capacity constra...
Article
Full-text available
Over the past two decades, equity aspects have been considered in a growing number of models and methods for vehicle routing problems (VRPs). Equity concerns most often relate to fairly allocating workloads and to balancing the utilization of resources, and many practical applications have been reported in the literature. However, there has been on...
Article
Full-text available
This paper introduces a genetic search-based heuristic to solve an offshore supply vessel planning problem (SVPP) faced by the Norwegian oil and gas company Statoil. The aim is to help the company in determining the optimal size of supply vessels to charter in and their corresponding voyages and schedules. We take inspiration from the hybrid geneti...
Article
Full-text available
We consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. T...
Article
Full-text available
Real-life problems are often characterized by conflicting optimization objectives. Consequently, there has been a growing interest not only in multi-objective models, but also in specialized multi-objective metaheuristics for solving those models. A wide variety of methods, e.g. NSGA-II, SPEA, IBEA, scatter search, Pareto local search, and many oth...
Article
Full-text available
This article explores a structural neighborhood decomposition for arc routing problems, in which the decisions about traversal orientations during services are made optimally as part of neighbor evaluation procedures. Using memory structures, bidirectional dynamic programming, and lower bounds, we show that a large neighborhood involving classical...
Article
We study a convex resource allocation problem in which lower and upper bounds are imposed on partial sums of allocations. This model is linked to a large range of applications, including production planning, speed optimization, stratified sampling, support vector machines, portfolio management, and telecommunications. We propose an efficient gradie...
Article
Full-text available
The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the following drawbacks: (i) became too easy for current algorithms; (ii) are too artificial; (iii) are too homogeneous, not covering the wide range of characteristics found in real applications. We pr...
Article
We address the Unequal-Area Facility-Layout Problem (UA-FLP), which aims to dimension and locate rectangular facilities in an unlimited floor space, without overlap, while minimizing the sum of distances among facilities weighted by “material-handling” flows. We introduce two algorithmic approaches to address this problem: a basic Genetic Algorithm...
Article
Full-text available
In this paper, we address two optimisation problems arising in the context of city logistics and two-level transportation systems. The two-echelon vehicle routing problem and the two-echelon location routing problem seek to produce vehicle itineraries to deliver goods to customers, with transits through intermediate facilities. To efficiently solve...
Article
Full-text available
Recently, equity aspects have been considered in a growing number of models and methods for vehicle routing problems (VRPs). Equity concerns most often relate to fairly allocating workloads and to balancing the utilization of resources, and many practical applications have been reported. However, there has been only limited discussion about how equ...
Article
We propose exact solution approaches for a lateral transhipment problem which, given a pre-specified sequence of customers, seeks an optimal inventory redistribution plan considering travel costs and profits dependent on inventory levels. Trip-duration and vehicle-capacity constraints are also imposed. The same problem arises in some lot sizing app...
Article
Full-text available
The Split algorithm is an essential building block for route-first cluster-second heuristics and modern genetic algorithms for vehicle routing problems. The recent survey of [Prins, Lacomme and Prodhon, Transport Res. C (40), 179-200] lists more than 70 articles that use this technique. Split is classically assimilated to the search for a shortest...
Article
Full-text available
Problem decomposition requires the ability to recombine partial solutions. This recombination task, which we call integration, is a fundamental feature of many methods, both those based on mathematical formulations such as Dantzig–Wolfe or Benders and those based on heuristics. Integration may be implicit in mathematical decompositions, but in heur...
Article
Full-text available
Timing problems involve the choice of task execution dates within a predetermined processing sequence, and under various additional constraints or objectives such as time windows, time-dependent costs, or flexible processing times, among others. Their efficient resolution is critical in branch and bound and neighborhood search methods for vehicle r...
Article
Full-text available
We propose a new speed and departure time optimization algorithm for the Pollution-Routing Problem (PRP) which runs in quadratic time. This algorithm is embedded into an iterated local search-based metaheuristic to achieve a combined speed, scheduling and routing optimization. Extensive computational experiments are conducted on classic PRP benchma...
Article
Full-text available
Onshore oil fields may contain hundreds of wells that use sophisticated and complex equipments. These equipments need regular maintenance to keep the wells at maximum productivity. When the productivity of a well decreases, a specially-equipped vehicle called a workover rig must visit this well to restore its full productivity. Given a heterogeneou...