Displaying similar documents to “The Chain-Interchange Heuristic Method”

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...

Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain

Yves Caseau (2006)

RAIRO - Operations Research

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This paper presents the approach that we developed to solve the ROADEF 2003 challenge problem. This work is part of a research program whose aim is to study the benefits and the computer-aided generation of hybrid solutions that mix constraint programming and meta-heuristics, such as large neighborhood search (LNS). This paper focuses on three contributions that were obtained during this project: an improved method for propagating Hamiltonian chain constraints, a fresh look at...

A memetic algorithm for the vehicle routing problem with time windows

Nacima Labadi, Christian Prins, Mohamed Reghioui (2008)

RAIRO - Operations Research

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This article deals with the vehicle routing problem with time windows (VRPTW). This problem consists in determining a least-cost set of trips to serve customers during specific time windows. The proposed solution method is a memetic algorithm (MA), a genetic algorithm hybridised with a local search. Contrary to most papers on the VRPTW, which minimize first the number of vehicles, our method is also able to minimize the total distance travelled. The results on 56 classical instances...

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...

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...

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...