A hybrid ACO approach to the matrix bandwidth minimization problem

Authors:
Camelia-M. Pintea;Gloria-Cerasela Crişan;Camelia Chira
Affiliations:
George Coşbuc N College, Cluj-Napoca, Romania;Vasile Alecsandri University, Bacău, Romania;Babeş-Bolyai University, Cluj-Napoca, Romania
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Year:
2010

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Abstract

The evolution of the human society raises more and more difficult endeavors For some of the real-life problems, the computing time-restriction enhances their complexity The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal The MBMP is a highly investigated ${\mathcal NP}$-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery This paper describes a new attempt to use the Ant Colony Optimization framework in tackling MBMP. The introduced model is based on the hybridization of the Ant Colony System technique with new local search mechanisms Computational experiments confirm a good performance of the proposed algorithm for the considered set of MBMP instances.