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Displaying similar documents to “Reservation table scheduling: branch-and-bound based optimization vs. integer linear programming techniques”

Scheduling multiprocessor tasks on two parallel processors

Jacek Błażewicz, Paolo Dell'Olmo, Maciej Drozdowski (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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In this work scheduling multiprocessor tasks on two parallel identical processors is considered. Multiprocessor tasks can be executed by more than one processor at the same moment of time. We analyze scheduling unit execution time and preemptable tasks to minimize schedule length and maximum lateness. Cases with ready times, due-dates and precedence constraints are discussed.

Consistency checking within local search applied to the frequency assignment with polarization problem

Michel Vasquez, Audrey Dupont, Djamal Habet (2003)

RAIRO - Operations Research - Recherche Opérationnelle

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We present a hybrid approach for the Frequency Assignment Problem with Polarization. This problem, viewed as Max-CSP, is treated as a sequence of decision problems, CSP like. The proposed approach combines the Arc-Consistency techniques with a performed Tabu Search heuristic. The resulting algorithm gives some high quality solutions and has proved its robustness on instances with approximately a thousand variables and nearly ten thousand constraints.

A branch-and-cut algorithm for a resource-constrained scheduling problem

Renaud Sirdey, Hervé L. M. Kerivin (2007)

RAIRO - Operations Research

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This paper is devoted to the exact resolution of a strongly -hard resource-constrained scheduling problem, the , which arises in relation to the operability of certain high-availability real-time distributed systems. Based on the study of the polytope defined as the convex hull of the incidence vectors of the admissible process move programs, we present a branch-and-cut algorithm along with extensive computational results demonstrating its practical relevance, in terms of both exact...

Multicriteria scheduling problems : a survey

V. T'kindt, J.-C. Billaut (2001)

RAIRO - Operations Research - Recherche Opérationnelle

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This paper presents a state-of-the-art survey on multicriteria scheduling and introduces a definition of a multicriteria scheduling problem. It provides a framework that allows to tackle multicriteria scheduling problems, according to Decision Aid concepts. This problem is decomposed into three different problems. The first problem is about obtaining a model. The second one is how to take criteria into account and the third one is about solving a scheduling problem. An extension to an...

France Telecom workforce scheduling problem: a challenge

Sebastian Pokutta, Gautier Stauffer (2009)

RAIRO - Operations Research

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In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic...

Evaluating the Kernighan-Lin heuristic for hardware/software partitioning

Zoltán Mann, András Orbán, Viktor Farkas (2007)

International Journal of Applied Mathematics and Computer Science

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In recent years, several heuristics have been proposed for the hardware/software partitioning problem. One of the most promising directions is the adaptation of the Kernighan-Lin algorithm. The Kernighan-Lin heuristic was originally developed for circuit partitioning, but it has been adapted to other domains as well. Moreover, numerous improvements have been suggested so that now several variants of the original algorithm exist. The aim of this paper is to systematically evaluate the...

A review on the ant colony optimization metaheuristic: basis, models and new trends.

Oscar Cordón, Francisco Herrera, Thomas Stützle (2002)

Mathware and Soft Computing

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Ant Colony Optimization (ACO) is a recent metaheuristic method that is inspired by the behavior of real ant colonies. In this paper, we review the underlying ideas of this approach that lead from the biological inspiration to the ACO metaheuristic, which gives a set of rules of how to apply ACO algorithms to challenging combinatorial problems. We present some of the algorithms that were developed under this framework, give an overview of current applications, and analyze the relationship...