Title

Integrated Genetic Algorithm with Hill Climbing for the Bandwidth Minimization Porblem

Publication Type

Conference Proceeding Article

Publication Date

7-2003

Abstract

In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Experiments show that this approach achieves the best solution quality when compared with the GPS [1] algorithm, Tabu Search [3], and the GRASP with Path Relinking methods [4], while being faster than the latter two newly-developed heuristics.

Discipline

Operations and Supply Chain Management

Research Areas

Operations Management

Publication

Genetic and Evolutionary Computation - GECCO 2003: Genetic and Evolutionary Computation Conference Chicago, IL, USA, July 12–16, 2003 Proceedings, Part II

Volume

2724

First Page

1594

Last Page

1595

ISBN

9783540451105

Identifier

10.1007/3-540-45110-2_41

Publisher

Springer

City or Country

Berlin

Additional URL

http://dx.doi.org/10.1007/3-540-45110-2_41