Displaying similar documents to “ACS-TS: Train scheduling using ant colony system.”

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...

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 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...

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.