Automatically assigned DDC number: 00633

Manually assigned DDC number: 00631

Number of references: 8

Title: Parallel Ant Colonies for Combinatorial Optimization Problems

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Subject: El-ghazali Talbi,Olivier Roux,Cyril Fonlupt,Denis Robillard Parallel Ant Colonies for Combinatorial Optimization Problems

Description: . Ant Colonies (AC) optimization take inspiration from the behavior of real ant colonies to solve optimization problems. This paper presents a parallel model for ant colonies to solve the quadratic assignment problem (QAP). Parallelism demonstrates that cooperation between communicating agents improve the obtained results in solving the QAP. It demonstrates also that high-performance computing is feasible to solve large optimization problems. 1 Introduction Many interesting combinatorial optimization problems are NP-hard, and then they cannot be solved exactly. Consequently, heuristics must be used to solve real-world problems within a reasonable amount of time. There has been a recent interest in the field of the Ant Colony Optimization (ACO). The basic idea is to imitate the cooperative behavior of ant colonies in order to solve combinatorial optimization problems within a reasonable amount of time. Ant Colonies (AC) is a general purpose heuristic (meta-heuristic) that has been prop...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1999-01-11

Pubyear: unknown

Format: ps

Identifier: http://citeseer.ist.psu.edu/173264.html

Source: http://www.lifl.fr/~talbi/ants98.ps.gz

Language: en

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