The problem of maximizing the minimal distance in Latin Hypercube Designs (maximin LHD) calls for arranging N points in a k-dimensional grid so that no pair of points share a coordinate and the minimal distance between all the pairs of points is as large as possible. Such problem is particularly relevant in designing computer experiments. In this paper we propose two Iterated Local Search (ILS) heuristics for this problem and show through some computational experiments that the proposed algorithms compare very well with different heuristic approaches in the established literature. © Springer Science+Business Media B.V. 2008.
Iterated local search approaches to maximin latin hypercube designs / Grosso, A.; Jamali, A. R. M. J. U.; Locatelli, M.. - (2008), pp. 52-56. (Intervento presentato al convegno 2007 International Conference on Systems, Computing Sciences and Software Engineering, SCSS 2007, Part of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, CISSE 2007 tenutosi a Bridgeport, CT, usa nel 2007) [10.1007/978-1-4020-8735-6_11].
Iterated local search approaches to maximin latin hypercube designs
Locatelli M.
2008-01-01
Abstract
The problem of maximizing the minimal distance in Latin Hypercube Designs (maximin LHD) calls for arranging N points in a k-dimensional grid so that no pair of points share a coordinate and the minimal distance between all the pairs of points is as large as possible. Such problem is particularly relevant in designing computer experiments. In this paper we propose two Iterated Local Search (ILS) heuristics for this problem and show through some computational experiments that the proposed algorithms compare very well with different heuristic approaches in the established literature. © Springer Science+Business Media B.V. 2008.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
