Authors: Pardo, Eduardo
Mladenović, Nenad 
Pantrigo, Juan
Duarte, Abraham
Title: Variable formulation search for the cutwidth minimization problem
Journal: Applied Soft Computing Journal
Volume: 13
Issue: 5
First page: 2242
Last page: 2252
Issue Date: 25-Mar-2013
Rank: M21
ISSN: 1568-4946
DOI: 10.1016/j.asoc.2013.01.016
Many optimization problems are formulated as min-max problems where the objective function consist of minimizing a maximum value. In this case, it is usual that many solutions of the problem has associated the same value of the objective function. When this happens it is difficult to determine which solution is more promising to continue the search. In this paper we propose a new variant of the Variable Neighbourhood Search methodology to tackle this kind of problems. The new variant, named Variable Formulation Search, makes use of alternative formulations of the problem to determine which solution is more promising when they have the same value of the objective function in the original formulation. We do that in shaking, local search and neighbourhood change steps of the basic Variable Neighbourhood Search. We apply the new methodology to the Cutwidth Minimization Problem. Computational results show that our proposal outperforms previous algorithms in the state of the art in terms of quality and computing time.
Keywords: Cutwidth Minimization Problem | Discrete optimization | Formulation Space Search | Variable Formulation Search | Variable Neighbourhood Search
Publisher: Elsevier

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