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September 2006 - August 2008

October 2002 - August 2006

## Publications

Publications (78)

Major advances were recently obtained in the exact solution of vehicle routing problems (VRPs). Sophisticated branch-cut-and-price (BCP) algorithms for some of the most classical VRP variants now solve many instances with up to a few hundreds of customers. However, adapting and reimplementing those successful algorithms for other variants can be a...

This document presents a user guide for BaPCod version 0.66, a C++ library implementing a generic branch-cut-and-price solver. We give guidelines for installing BaPCod, using its modelling language, BaPCod parameterization, retrieving BaPCod statistics, and understanding BaP-Cod output. We also present the VRPSolver extension of BaPCod which allows...

“Nonrobust Strong Knapsack Cuts for Capacitated Location Routing and Related Problems,” by Liguori et al., presents a novel BCP algorithm for the CLRP and for other problems that share a nested knapsack structure. It outperforms existing exact algorithms in the literature, making it a powerful tool for solving instances with a large number of depot...

Given the emergence of two-echelon distribution systems in several practical contexts, this paper tackles, at the strategic level, a distribution network design problem under uncertainty. This problem is defined as the two-echelon stochastic multi-period capacitated location-routing problem (2E-SM-CLRP). It considers a network partitioned into two...

We study the prize-collecting job sequencing problem with one common and multiple secondary resources. In this problem, a set of jobs is given, each with a profit, multiple time windows for its execution, and a duration during which it requires the main resource. Each job also requires a preassigned secondary resource before, during, and after its...

The optimization community has made significant progress in solving vehicle routing problems (VRPs) to optimality using sophisticated branch-cut-and-price (BCP) algorithms. VRPSolver is a BCP algorithm with excellent performance in many VRP variants. However, its complex underlying mathematical model makes it hardly accessible to routing practition...

We propose a new family of formulations with route-based variables for the split delivery vehicle routing problem with and without time windows. Each formulation in this family is characterized by the maximum number of different demand quantities that can be delivered to a customer during a vehicle visit. As opposed to previous formulations in the...

In this article, we propose graph‐based models for several vehicle routing problems with intermediate stops: the capacitated multi‐trip vehicle routing problem with time windows, the multi‐depot vehicle routing problem with inter‐depot routes, the arc routing problem with intermediate facilities under capacity and length restrictions and the green...

We introduce and motivate several variants of the bin packing problem where bins are assigned to time slots, and minimum and maximum lags are required between some pairs of items. We suggest two integer programming formulations for the general problem: a compact one and a stronger formulation with an exponential number of variables and constraints....

The paper studies the two-echelon capacitated vehicle routing problem with time windows, in which delivery of freight from depots to customers is performed using intermediate facilities called satellites. We consider the variant of the problem with precedence constraints for unloading and loading freight at satellites. In this variant allows for st...

This work proposes a partial optimization metaheuristic under special intensification conditions (POPMUSIC) for the classical capacitated vehicle routing problem. The proposed approach uses a branch-cut-and-price algorithm as a powerful heuristic to solve subproblems whose dimensions are typically between 25 and 200 customers. The whole algorithm c...

We propose branch-cut-and-price algorithms for the classic bin packing problem and also for the following related problems: vector packing, variable sized bin packing, and variable sized bin packing with optional items. The algorithms are defined as models for VRPSolver, a generic solver for vehicle routing problems. In that way, a simple parameter...

More than ever, data networks have demonstrated their central role in the world economy, but also in the well-being of humanity that needs fast and reliable networks. In parallel, with the emergence of Network Function Virtualization (NFV) and Software Defined Networking (SDN), efficient network algorithms considered too hard to be put in practice...

Capacitated vehicle routing problems are widely studied combinatorial optimization problems, and branch-and-cut-and-price algorithms can solve instances harder than ever before. These models, however, neglect that demands volumes are often not known with precision when planning the vehicle routes, thus incentivizing decision makers to significantly...

This work proposes a partial optimization metaheuristic under special intensification conditions (POPMUSIC) for the classical capacitated vehicle routing problem (CVRP). The proposed approach uses a branch-cut-and-price algorithm as a powerful heuristic to solve subproblems whose dimensions are typically between 25 and 200 customers. The whole algo...

We consider the Shortest Path Problem with Resource Constraints (SPPRC) arising as a subproblem in state-of-the-art Branch-Cut-and-Price algorithms for vehicle routing problems. We propose a variant of the bi-directional label correcting algorithm in which the labels are stored and extended according to the so-called bucket graph. Such organization...

This work deals with a very generic class of scheduling problems with identical/uniform/unrelated parallel machine environment. It considers well-known attributes such as release dates, deadlines, or sequence-dependent setup times and accepts any objective function defined over job completion times. Non-regular objectives are also supported. We int...

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...

In a personal communication with Ruslan Sadykov from Inria, France, we found an implementation error in our code for importing the benchmark instance set MUT leading to wrong numerical results in our original article (Gouveia, Leitner, and Ruthmair, 2017). In this corrigendum we provide corrected results for all experiments on instance set MUT. The...

In the paper, we propose a branch-cut-and-price algorithm for the two-echelon capacitated vehicle routing problem in which delivery of products from a depot to customers is performed using intermediate depots called satellites. Our algorithm incorporates significant improvements recently proposed in the literature for the standard capacitated vehic...

In the two-dimensional guillotine cutting-stock problem, the objective is to minimize the number of large plates used to cut a list of small rectangles. We consider a variant of this problem, which arises in glass industry when different bills of order (or batches) are considered consecutively. For practical organization reasons, leftovers are not...

Math heuristics have become an essential component in mixed integer programming (MIP) solvers. Extending generic MIP heuristics, our study outlines generic procedures to build primal solutions in the context of a Branch-and-Price approach and reports on their performance. Rounding the linear relaxation solution of the Dantzig-Wolfe reformulation, w...

Major advances were recently obtained in the exact solution of Vehicle Routing Problems (VRPs). Sophisticated Branch-Cut-and-Price (BCP) algorithms for some of the most classical VRP variants now solve many instances with up to a few hundreds of customers. However, adapting and reimplementing those successful algorithms for other variants can be a...

The convergence of a column generation algorithm can be improved in practice by using so-called stabilization techniques. Proximal methods based on penalising the deviation from the incumbent dual solution have become standards of the domain. However, the analysis of such methods is important to understand the mechanism on which they rely, to appre...

This paper deals with the Minimum Latency Problem (MLP), a variant of the well-known Travel-ing Salesman Problem in which the objective is to minimize the sum of waiting times of customers. This problem arises in many applications where customer satisfaction is more important than the total time spent by the server. This paper presents a novel bran...

This paper considers a family of Vehicle Routing Problem (VRP) variants that generalize the classical Capacitated VRP by taking into account the possibility that vehicles differ by capacity, costs, depot allocation, or even by the subset of customers that they can visit. This work proposes a Branch-Cut-and-Price algorithm that adapts advanced featu...

The two-dimensional knapsack problem consists in packing a set of small rectangular items into a given large rectangle while maximizing the total reward associated with selected items. We restrict our attention to packings that emanate from a k-stage guillotine-cut process. We introduce a generic model where a knapsack solution is represented by a...

We consider the flowshop problem on two machines with sequence-independent setup times to minimize total completion time. Large scale network flow formulations of the problem are suggested together with strong Lagrangian bounds based on these formulations. To cope with their size, filtering procedures are developed. To solve the problem to optimali...

In this paper, we address a multi-activity tour scheduling problem with time varying demand. The objective is to compute a team schedule for a fixed roster of employees in order to minimize the over-coverage and the under-coverage of different parallel activity demands along a planning horizon of one week. Numerous complicating constraints are pres...

This study will propose a new Lagrangian bound for the min-sum job-shop scheduling problem. The proposed method is an integration of two types of Lagrangian relaxation methods known as job-level and machine-level decomposition methods. It will be shown by numerical experiments that the proposed method can improve the existing lower bounds significa...

In this paper, we address a multi-activity tour scheduling problem with time varying demand. The objective is to compute a team schedule for a fixed roster of employees in order to minimize the over-coverage and the under-coverage of different parallel activity demands along a planning horizon of one week. Numerous complicating constraints are pres...

We consider a variant of the freight railcar flow problem. In this problem, we need 1) to chose a set of transportation demands between stations in a railroad network, and 2) to fulfill these demands by appropriately routing the set of available railcars, while maximizing the total profit. We formulate this problem as a multi-commodity flow problem...

Stabilization procedures for column generation can be viewed as cutting plane strategies in the dual. Exploiting the link between in-out separation strategies and dual price smoothing techniques for column generation, we derive a generic bound convergence property for algorithms using a smoothing feature. Such property adds to existing in-out asymp...

Working in an extended variable space allows one to develop tighter reformu-lations for mixed integer programs. However, the size of the extended formulation grows rapidly too large for a direct treatment by a MIP-solver. Then, one can work with inner approximations defined and improved by generating dynamically vari-ables and constraints. When the...

Cross docking terminals allow companies to reduce storage and transportation costs in a supply chain. At these terminals, products of different types from incoming trucks are unloaded, sorted, and loaded to outgoing trucks for delivery. If the designated outgoing truck is not immediately available for some products, they are temporarily stocked in...

Primal heuristics have become an essential component in mixed integer programming (MIP). Generic heuristic paradigms of the literature remain to be extended to the context of a column generation so-lution approach. As the Dantzig-Wolfe reformulation is typically tighter than the original compact formulation, techniques based on rounding its linear...

This paper is about scheduling parallel jobs, i.e. which can be executed on more than one machine at the same time. Malleable jobs is a special class of parallel jobs. The number of machines a malleable job is executed on may change during its execution.In this work, we consider the NP-hard problem of scheduling malleable jobs to minimize the total...

The bin packing problem with conflicts consists in packing items in a minimum number of bins of limited capacity while avoiding joint assignments of items that are in conflict. Our study demonstrates the comparatively good performance of a generic Branch-and-Price algorithm for this problem. We made use of our black-box solver BaPCod, relying on it...

Working in an extended variable space allows one to develop tight reformulations for mixed integer programs (MIP). However, the size of the extended formulation grows rapidly too large for a direct treatment by a MIP-solver. When the extended formulation stems from a decomposition principle, as typical in practice, a column generation procedure tha...

In the past decade, significant progress has been achieved in developing generic primal heuristics that made their way into commercial mixed integer programming (MIP) solver. Extensions to the context of a column generation solution approach are not straightforward. The Dantzig-Wolfe decomposition principle can indeed be exploited in greedy, local...

Airborne radars are widely used to perform a large variety of tasks in an aircraft (searching, tracking, identifying targets, etc.) Such tasks play a crucial role for the aircraft and they are repeated in a "more or less" cyclic fashion. This defines a scheduling problem that impacts a lot on the quality of the radar output and on the overall safet...

We study the scheduling situation in which a set of jobs subjected to release dates and deadlines are to be performed on a single machine. The objective is to minimize a piecewise linear objective function ∑jFj where Fj(Cj) corresponds to the cost of the completion of job j at time Cj. This class of function is very large and thus interesting both...

This paper is about scheduling parallel jobs, i.e. which can be executed on more than one processor at the same time. Malleable jobs is a special class of parallel jobs. The number of processors a malleable job is executed on may change during the execution. In this work, we consider the NP-hard problem of scheduling malleable jobs to minimize the...

At cross docking terminals, products from incoming trucks are sorted according to there destinations and transferred to outgoing trucks using a temporary storage. Such terminals allow companies to reduce storage and transportation costs in supply chain. This paper focuses on the operational activities at cross docking terminals. We consider the tru...

In this paper we consider the scheduling problem of minimizing the weighted number of late jobs on a single machine (1rj[summation operator]wjUj). A branch-and-check algorithm is proposed, where a relaxed integer programming formulation is solved by branch-and-bound and infeasible solutions are cut off using infeasibility cuts. We suggest two ways...

The strongly NP-hard scheduling problem of minimizing the maximum lateness on one machine subject to job release dates is
under study. We present a general scheme of approximation solution of the problem which is based on searching for a given
problem instance another instance, closest to the original in some metric and belonging to a known polynom...

e consider both branch-and-cut and column-generation approaches for the problem of finding a minimum- cost assignment of jobs with release dates and deadlines to unrelated parallel machines. Results are presented for several variants both with and without constraint programming. Among the variants, the most effective strategy is to combine a tight...

In this paper we consider the scheduling problem of minimizing the sum of the weights of the late jobs on a single machine (1|rj| [sum] wj Uj ). A branch-and-check algorithm is proposed, where a relaxed integer programming formulation is solved by branch-and-bound and infeasible solutions are cut off using unfeasibility cuts. We suggest two ways to...

We consider the scheduling problem of minimizing the weighted sum of late jobs on a single machine (1| r
j
| sumw
j
U
j
). A hybrid Branch-and-Cut algorithm is proposed, where infeasibility cuts are generated using CP. Two ways are suggested to increase the strength of cuts. The proposed approach has been implemented in the Mosel modelling and opti...

At cross docking terminals, products from incoming trucks are sorted ac-cording to their destinations and transferred to outgoing trucks using a small temporary storage. Such terminals allow companies to reduce storage and transportation costs in a supply chain. This paper focuses on the operational activities at cross docking terminals. We conside...

Abstract We present new MIP formulations for the single machine total weighted tardiness problem. These formulations are based on a partition of the time horizon into intervals. This partition is done in such a way that the problem reduces to the problem of assigning jobs to intervals. This leads to a compact formulation that can be solved with sta...