Anatomy of the Attraction Basins: Breaking with the Intuition.

Permutation-based combinatorial optimization problems attraction basins landscape visualization. local optima local search

Journal

Evolutionary computation
ISSN: 1530-9304
Titre abrégé: Evol Comput
Pays: United States
ID NLM: 9513581

Informations de publication

Date de publication:
2019
Historique:
pubmed: 23 5 2018
medline: 12 2 2020
entrez: 23 5 2018
Statut: ppublish

Résumé

Solving combinatorial optimization problems efficiently requires the development of algorithms that consider the specific properties of the problems. In this sense, local search algorithms are designed over a neighborhood structure that partially accounts for these properties. Considering a neighborhood, the space is usually interpreted as a natural landscape, with valleys and mountains. Under this perception, it is commonly believed that, if maximizing, the solutions located in the slopes of the same mountain belong to the same attraction basin, with the peaks of the mountains being the local optima. Unfortunately, this is a widespread erroneous visualization of a combinatorial landscape. Thus, our aim is to clarify this aspect, providing a detailed analysis of, first, the existence of plateaus where the local optima are involved, and second, the properties that define the topology of the attraction basins, picturing a reliable visualization of the landscapes. Some of the features explored in this article have never been examined before. Hence, new findings about the structure of the attraction basins are shown. The study is focused on instances of permutation-based combinatorial optimization problems considering the 2-exchange and the insert neighborhoods. As a consequence of this work, we break away from the extended belief about the anatomy of attraction basins.

Identifiants

pubmed: 29786459
doi: 10.1162/evco_a_00227
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

435-466

Auteurs

Leticia Hernando (L)

Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, 20018 San Sebastián, Spain leticia.hernando@ehu.eus.

Alexander Mendiburu (A)

Intelligent Systems Group, Department of Computer Architecture and Technology, University of the Basque Country UPV/EHU, 20018 San Sebastián, Spain alexander.mendiburu@ehu.eus.

Jose A Lozano (JA)

Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, 20018 San Sebastián, Spain Basque Center for Applied Mathematics (BCAM), 48009 Bilbao, Spain ja.lozano@ehu.eus.

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Classifications MeSH