Métaheuristiques pour l'ordonnancement biobjectif de type flowshop

Pour assurer une production de biens de qualité, de manière fiable et dans des délais maîtrisés, les organisations ont besoin d’outils d\u27exécution optimale de tâches tels que l’ordonnancement. Le succès des méthodologies de résolution des problèmes d’ordonnancement de production basées sur les métaheuristiques s’explique par leur capacité à fournir des solutions proches de l’optimum, dans des temps raisonnables. Cet ouvrage se consacre, dans un premier temps, aux métaheuristiques appliquées aux problèmes d’ordonnancement multicritère, qui sont des cas particuliers des problèmes d’optimisation combinatoire multicritère, généralement NP-difficiles. Puis, il s’intéresse aux préoccupations d’ordonnancement dans le secteur du transport qui suscitent également de multiples problèmes d’optimisation. Deux grands domaines d’application se distinguent, celui des systèmes de transport et celui des ressources de transport intervenant dans un atelier

Recherche locale multi-objectif basée sur les ensembles

Date du colloque : 04/2012National audienc

About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework

Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and other related components. Most of these tools follow a monolithic architecture that frequently leads to a lack of flexibility when a user intends to add new features to the included algorithms. In this paper, we explore a different approach by designing a component-based architecture for a multi-objective optimization framework based on the observer pattern. In this architecture, most of the algorithmic components are observable entities that naturally allows to register a number of observers. This way, a metaheuristic is composed of a set of observable and observer elements, which can be easily extended without requiring to modify the algorithm. We have developed a prototype of this architecture and implemented the NSGA-II evolutionary algorithm on top of it as a case study. Our analysis confirms the improvement of flexibility using this architecture, pointing out the requirements it imposes and how performance is affected when adopting it.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem

International audienceMultiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances

MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

International audienceAutomated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator

Ressources cognitives et développement territorial : une analyse textuelle appliquée aux politiques locales de développement durable

International audienceThis paper focuses on how the development of a particular region consistently requires actors to share a certain level of cognitive resources. In the case studied here - the Nord Pas-de-Calais region, this cognitive proximity is built via the local policies involving sustainable development. In order to comprehend the way local communities of the region activate this resource, we used textual data treatment analyzing about thirty interviews. The results suggest that this cognitive proximity relies on two fundamentals elements: on the one hand, valuing the patrimonial infrastructures of the territory; and on the other hand, rebuilding the territorial identity of the region. Then the local policies lean both on the values that underlie these elements and on rhetorical modalities, to impulse in-depth changes that would have been more difficult to implement from the usual political levers.Cet article étudie comment un développement régional cohérent nécessite la mobilisation de ressources cognitives partagées. Dans le cas étudié - la région Nord Pas-de-Calais, cette proximité cognitive se construit via les politiques locales, sur la base du référentiel de développement durable. Pour saisir la manière dont les collectivités de la région activent cette ressource, nous avons mobilisé les outils d'analyse textuelle sur une trentaine d'entretiens auprès des acteurs publics du développement durabe. Les résultats mis en évidence suggèrent que cette proximité cognitive repose sur deux éléments fondamentaux : d'une part la mise en valeur d'un patrimoine infrastructurel territorialisé, et d'autre part la reconstruction d'une identité territoriale. Les politiques locales prennent ainsi appui sur les valeurs qui sous-tendent ces éléments ainsi que sur des modalités rhétoriques, pour impulser en profondeur une dynamique de changement, plus malaisée à mettre en œuvre partir des outils politiques habituels

A practical case of the multiobjective knapsack problem: Design, modelling, tests and analysis

In this paper, we present a practical case of the multiobjective knapsack problem which concerns the elaboration of the optimal action plan in the social and medico-social sector. We provide a description and a formal model of the problem as well as some preliminary computational results. We perform an empirical analysis of the behavior of three metaheuristic approaches: a fast and elitist multiobjective genetic algorithm (NSGA-II), a Pareto Local Search (PLS) algorithm and an Indicator-Based Multi-Objective Local Search (IBMOLS)

A Bug in the Multiobjective Optimizer IBEA: Salutary Lessons for Code Release and a Performance Re-Assessment

International audienceThe Indicator-Based Evolutionary Algorithm (IBEA) is one of the first indicator-based multiobjective optimization algorithms and due to its wide availability in several algorithm packages is often used as a reference algorithm when benchmarking multiobjective optimizers. The original publication on IBEA proposes to use two specific variants: one based on the ε-indicator and one based on the hypervolume. Several experimental studies concluded that, surprisingly, the IBEA variant with the ε-indicator performs better than the one with the hypervolume—even if the (unary) hypervolume indicator itself is the quality measure used in the performance assessment. Recently, a small bug has been found in the hypervolume variant of IBEA with large implications on its performance. Here, we not only explain the bug in detail and correct it, but also present the (improved) results of the corrected version. Moreover, and probably even more important for the scientific community, we point out that this bug has been transferred to other than the original software package, discuss how this obscured the bug, and argue in favor of some simple, even obvious guidelines how the optimization community should deal with algorithm source codes, documentation, and the (natural) existence of bugs in the future