Métaheuristiques pour l'allocation de mémoire dans les systèmes embarqués

National audienceLa gestion de la mémoire cache a un impact significatif sur les performances et sur la consommation énergétique des systèmes embarqués. Cet article traite de l'allocation de mémoire des structures de données d'une application à la mémoire cache de manière à optimiser les performances du système. Les concepteurs de circuits souhaitent trouver un compromis entre le coût de l'architecture (le nombre de bancs mémoire à embarquer) et la consommation électrique. Le problème abordé consiste à allouer un banc mémoire à toute structure de données de manière à minimiser les conflits d'accès aux données. Le modèle proposé pour ce problème est le k-weighted graph coloring problem. Une formulation par PLNE et deux métaheuristiques basées respectivement sur une recherche taboue et sur un algorithme hybride à base de population sont comparées sur un ensemble d'instances. Les résultats obtenus sont encourageants et suggèrent que l'utilisation de méthodes issues de la coloration de graphes est une piste prometteuse pour l'allocation de mémoire dans les systèmes embarqués

Performance Guarantees of Local Search for Multiprocessor Scheduling

Increasing interest has recently been shown in analyzing the worst-case behavior of local search algorithms. In particular, the quality of local optima and the time needed to find the local optima by the simplest form of local search has been studied. This paper deals with worst-case performance of local search algorithms for makespan minimization on parallel machines. We analyze the quality of the local optima obtained by iterative improvement over the jump, swap, multi-exchange, and the newly defined push neighborhoods. Finally, for the jump neighborhood we provide bounds on the number of local search steps required to find a local optimum.operations research and management science;

Applications of Mathematical Programming in Personnel Scheduling

In the few decades of its existence, mathematical programming has evolved into an important branch of operations research and management science. This thesis consists of four papers in which we apply mathematical programming to real-life personnel scheduling and project management problems. We develop exact mathematical programming formulations. Furthermore, we propose effective heuristic strategies to decompose the original problems into subproblems that can be solved effciently with tailored mathematical programming formulations. We opt for solution methods that are based on mathematical programming, because their advantages in practice are a) the exibility to easily accommodate changes in the problem setting, b) the possibility to evaluate the quality of the solutions obtained, and c) the possibility to use general-purpose solvers, which are often the only software available in practice

Jan Karel Lenstra : the traveling science man : liber amicorum

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On local search for the generalized graph coloring problem

Given an edge-weighted graph and an integer k, the generalized graph coloring problem is the problem of partitioning the vertex set into k subsets so as to minimize the total weight of the edges that are included in a single subset. We recall a result on the equivalence between karush–kuhn–tucker points for a quadratic programming formulation and local optima for the simple flip-neighborhood. We also show that the quality of local optima with respect to a large class of neighborhoods may be arbitrarily bad and that some local optima may be hard to find