Displaying similar documents to “Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain ”

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.

Reservation table scheduling: branch-and-bound based optimization . integer linear programming techniques

Hadda Cherroun, Alain Darte, Paul Feautrier (2007)

RAIRO - Operations Research

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The recourse to operation research solutions has strongly increased the performances of scheduling task in the High-Level Synthesis (called hardware compilation). Scheduling a whole program is not possible as too many constraints and objectives interact. We decompose high-level scheduling in three steps. Step 1: Coarse-grain scheduling tries to exploit parallelism and locality of the whole program (in particular in loops, possibly imperfectly nested) with a rough view of the target...

Experiments with variants of ant algorithms.

Thomas Stützle, Sebastian Linke (2002)

Mathware and Soft Computing

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A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were proposed in the literature. These extensions typically achieve much improved computational results when compared to the original Ant System. However, many design choices of Ant System are left untouched including the fact that solutions are constructed, that real-numbers are used to simulate pheromone trails, and that explicit pheromone evaporation is used. In this article we experimentally...

Adaptive search heuristics for the generalized assignment problem.

Helena Ramalhinho Lourenço, Daniel Serra (2002)

Mathware and Soft Computing

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The Generalized Assignment Problem consists of assigning a set of tasks to a set of agents at minimum cost. Each agent has a limited amount of a single resource and each task must be assigned to one and only one agent, requiring a certain amount of the agent's resource. We present the application of a MAX-MIN Ant System (MMAS) and a greedy randomized adaptive search procedure (GRASP) to the generalized assignment problem based on hybrid approaches. The MMAS heuristic can be seen as an...

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...

About the choice of the variable to unassign in a decision repair algorithm

Cédric Pralet, Gérard Verfaillie (2005)

RAIRO - Operations Research - Recherche Opérationnelle

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The decision repair algorithm (Jussien and Lhomme, Artificial Intelligence 139 (2002) 21–45), which has been designed to solve constraint satisfaction problems (CSP), can be seen, either (i) as an extension of the classical depth first tree search algorithm with the introduction of a free choice of the variable to which to backtrack in case of inconsistency, or (ii) as a local search algorithm in the space of the partial consistent variable assignments. or (iii) as a hybridisation between...