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Conference Paper (published)

Sampling local optima networks of large combinatorial search spaces: The qap case

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Citation

Verel S, Daolio F, Ochoa G & Tomassini M (2018) Sampling local optima networks of large combinatorial search spaces: The qap case. In: Fonseca C, Lourenco N, Machado P, Paquete L, Auger A & Whitley D (eds.) Parallel Problem Solving from Nature – PPSN XV. PPSN 2018. Lecture Notes in Computer Science, 11102. PPSN 2018: International Conference on Parallel Problem Solving from Nature, Coimbra, Portugal, 08.09.2018-12.09.2018. Cham, Switzerland: Springer Verlag, pp. 257-268. https://doi.org/10.1007/978-3-319-99259-4_21

Abstract
Local Optima Networks (LON) model combinatorial landscapes as graphs, where nodes are local optima and edges transitions among them according to given move operators. Modelling landscapes as networks brings a new rich set of metrics to characterize them. Most of the previous works on LONs fully enumerate the underlying landscapes to extract all local optima, which limits their use to small instances. This article proposes a sound sampling procedure to extract LONs of larger instances and estimate their metrics. The results obtained on two classes of Quadratic Assignment Problem (QAP) benchmark instances show that the method produces reliable results.

StatusPublished
Title of seriesLecture Notes in Computer Science
Number in series11102
Publication date31/12/2018
Publication date online21/08/2018
URL
PublisherSpringer Verlag
Place of publicationCham, Switzerland
ISSN0302-9743
ISSN of series0302-9743
ISBN0302-9743
ConferencePPSN 2018: International Conference on Parallel Problem Solving from Nature
Conference locationCoimbra, Portugal
Dates

People (1)

Professor Gabriela Ochoa

Professor Gabriela Ochoa

Professor, Computing Science

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