Eric Bourreau

Exact approaches for lifetime maximization in connectivity constrained wireless multi-role sensor networks

In this paper, we consider the duty scheduling of sensor activities in wireless sensor networks to maximize the lifetime. We address full target coverage problems contemplating sensors used for sensing data and transmit it to the base station through multi-hop communication as well as sensors used only for communication purposes. Subsets of sensors (also called covers) are generated. Those covers are able to satisfy the coverage requirements as well as the connection to the base station. Thus, maximum lifetime can be obtained by identifying the optimal covers and allocate them an operation time. The problem is solved through a column generation approach decomposed in a master problem used to allocate the optimal time interval during which covers are used and in a pricing subproblem used to identify the covers leading to maximum lifetime. Additionally, Branch-and-Cut based on Benders’ decomposition and constraint programming approaches are used to solve the pricing subproblem. The approach is tested on randomly generated instances. The computational results demonstrate the efficiency of the proposed approach to solve the maximum network lifetime problem in wireless sensor networks with up to 500 sensors.

Machine reassignment problem: the ROADEF/EURO challenge 2012

The ROADEF/EURO challenge is a contest jointly organized by the French Operational Research and Decision Aid society (ROADEF) and the European Operational Research society (EURO). The contest appears on a regular basis since 1999 and always concerns an industrial optimization problem proposed by an industrial partner. Google proposed a subject for the ROADEF/EURO challenge 2012 (http://challenge.roadef.org/2012/en/), presenting a complex and large-scale machine reassignment problem, where a set of processes assigned to a set of machines have to be reassigned (or moved) while balancing machine usage improvement and moving costs, under resource (more precisely CPU, RAM, disk) and operational constraints. The 2012 challenge edition has been an unprecedented success with 82 registered teams, 48 teams that actually sent a program for qualification, 30 qualified teams and 27 teams that sent a program for the final evaluation. This paper aims at introducing the Annals of Operations Research special issue by presenting the ROADEF/EURO challenge 2012 subject, as well as the methods of the finalist teams and their results.

The TV-Break Packing Problem

Abstract Instead of selling advertisement spots one by one, some French satellite channels decided in 2002 to modify their commercial offer in order to sell packages of spots. These new general conditions of sale lead to an interesting optimization problem that we named the TV-B reak P acking P roblem (TVBP). We establish its NP-hardness and study various resolutions approaches including linear programming (LP), Lagrangian relaxation (LR), constraint programming (CP) and local search (LS). Finally we propose a generic CP/LS hybridization scheme (branch and move) whose application to the TVBP obtained the best results in our experiments. Dual upper bounds of the maximal revenue are also computed.

Disruption management for commercial airlines: methods and results for the ROADEF 2009 Challenge

A disruption management problem for commercial airlines has been presented by Amadeus for the ROADEF 2009 Challenge, an international competition organised by the French Operational Research and Decision Support Society (ROADEF). This paper presents this industrial large scale optimisation problem and underlines its difficulties compared to previously tackled problems in the area. We review the most prominent methods proposed by the candidates and provide the official results and participant ranking. Last, as lessons learned from this experience, we draw guidelines for further research. [Received 11 November 2009; Revised 4 June 2010; Accepted 29 November 2010]

Partial target coverage to extend the lifetime in wireless multi-role sensor networks

This article studies the effect of partial coverage to extend the lifetime of wireless sensor networks and introduces a hybrid exact solution strategy that efficiently maximizes network lifetime. We consider a set of sensors used to provide coverage of discrete targets and transfer the information to the sink node via multi-hop wireless communication. An active sensor has one of the two roles: it is a source when it senses and transfers data; it is a relay if it only transfers data. Network lifetime is extended through the use of covers representing sensors role allocation and network topology. A hybrid column generation is used to identify the optimal operation schedules and roles allocation that maximize network lifetime. A constraint programming strategy is provided to identify profitable network configurations leading to extend network lifetime and to prove optimality of the solutions found. Moreover, an evolutionary algorithm is proposed to boost up the solution process and accelerate convergence. Extensive computational results demonstrate the effectiveness of the proposed approach.

Instantiation of meta-models constrained with OCL: A CSP approach

The automated generation of models that conform to a given meta-model is an important challenge in Model Driven Engineering, as well for model transformation testing, as for designing and exploring new meta-models. Amongst the main issues, we are mainly concerned by scalability, flexibility and a reasonable computing time. This paper presents an approach for model generation, which relies on Constraint Programming. After the translation of a meta-model into a CSP, our software generates models that conform to this meta-model, using a Constraint Solver. Our model also includes the most frequent types of OCL constraints. Since we are concerned by the relevance of the produced models, we describe a first attempt to improve them. We outperform the existing approaches from the mentioned point of view, and propose a configurable, easy-to-use and free-access tool, together with an on-line demonstrator.

A Model-Driven Approach to Generate Relevant and Realistic Datasets

Disposing of relevant and realistic datasets is a difficult challenge in many areas, for benchmarking or testing purpose. Datasets may contain complexly structured data such as graphs or models, and obtaining such kind of data is sometimes expensive and available benchmarks are not as relevant as they should be. In this paper we propose a model-driven approach based on a probabilistic simulation using domain specific metrics for automated generation of relevant and realistic datasets.

Improvement proposals to intrinsically motivational robotics

In this paper, we first give a brief background on artificial curiosity and intrinsic motivation as it is studied in the developmental robotics research community. We then introduce some theoretical improvements for mechanisms related to intrinsically motivational living algorithms as introduced by SAGG-RIAC algorithm. Finally we conclude by drawing the way for our future experimental results using these new improvements.

FIMO: Framework for Intrinsic Motivation

This paper aims to introduce a flexible framework called FIMO dedicated to intrinsic motivation in developmental robotics. With this framework we want to offer a common way of implementing, testing and analyzing mechanisms related to intrinsically motivated algorithms. It may be seen as a generic complex open source framework for online exploration and structuring of learning spaces. We hereby lay both theoretical and practical foundations of our framework to encourage future experimental studies.

Trains do not vanish: the ROADEF/EURO challenge 2014

The ROADEF/EURO challenge is a contest jointly organized by the French Operational Research and Decision Aid society (ROADEF) and the European Operational Research society (EURO). The contest has appeared on a regular basis since 1999 and always concerns an applied optimization problem proposed by an industrial partner. The 2014 edition of the ROADEF/EURO challenge was led by the Innovation & Research department of SNCF, a global leader in passenger and freight transport services, and infrastructure manager of the French railway network. The objective of the challenge was to find the best way to store and move trains on large railway sites, between their arrivals and departures. Since trains never vanish and traffic continues to increase, in recent years some stations have been having real congestion issues. Train management in large railway sites is of high interest for SNCF, which is why it was submitted to the operations research community as the industrial problem for the 2014 edition of the ROADEF/EURO challenge. This paper introduces the special section of the Annals of Operations Research volume devoted to the ROADEF/EURO challenge 2014, as well as the methods of the finalist teams and their results.