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A hybrid local search algorithm for minimum dominating set problems

Minimum dominating set (MDS) is a well-known NP-hard fundamental graph theory problem having many applications such as mining social networks and bioinformatics. MDS seeks for the minimum subset of vertices in which every vertex not in the selected subset is adjacent to at least one vertex of this s...

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Main Authors:	Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.
Format:	Article
Published:	Elsevier Ltd 2022
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132527008&doi=10.1016%2fj.engappai.2022.105053&partnerID=40&md5=3039d1f8630093a54635c16e891d1c95 http://eprints.utp.edu.my/33322/
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spelling	my.utp.eprints.333222022-07-26T06:40:26Z A hybrid local search algorithm for minimum dominating set problems Abed, S.A. Rais, H.M. Watada, J. Sabar, N.R. Minimum dominating set (MDS) is a well-known NP-hard fundamental graph theory problem having many applications such as mining social networks and bioinformatics. MDS seeks for the minimum subset of vertices in which every vertex not in the selected subset is adjacent to at least one vertex of this subset. In this study, we consider MDS and a complex variant of MDS known as the minimum positive influence dominating set (MPIDS). In MPIDS, the aim is to identify a subset of vertices where each vertex of a graph must be dominated by at least half of its neighbors. To solve these problems, we propose a two-stage hybrid local search algorithm. In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. Moreover, we introduce information content strategy-based neighborhood structure and tolerance-based features to evolve high-quality and diverse solutions. For the second stage, we propose a gain-based deterministic local search algorithm as an exploitation procedure. It navigates feasible neighborhood areas to improve the solution quality. We conducted extensive analysis to evaluate the impact of the proposed components. The proposed algorithm produced very good results and generalized well overall instances of both MDS and MPIDS. Compared to the literature, the proposed algorithm outperformed other algorithms in most of the tested instances. Â© 2022 Elsevier Ltd Elsevier Ltd 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132527008&doi=10.1016%2fj.engappai.2022.105053&partnerID=40&md5=3039d1f8630093a54635c16e891d1c95 Abed, S.A. and Rais, H.M. and Watada, J. and Sabar, N.R. (2022) A hybrid local search algorithm for minimum dominating set problems. Engineering Applications of Artificial Intelligence, 114 . http://eprints.utp.edu.my/33322/
institution	Universiti Teknologi Petronas
building	UTP Resource Centre
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Petronas
content_source	UTP Institutional Repository
url_provider	http://eprints.utp.edu.my/
description	Minimum dominating set (MDS) is a well-known NP-hard fundamental graph theory problem having many applications such as mining social networks and bioinformatics. MDS seeks for the minimum subset of vertices in which every vertex not in the selected subset is adjacent to at least one vertex of this subset. In this study, we consider MDS and a complex variant of MDS known as the minimum positive influence dominating set (MPIDS). In MPIDS, the aim is to identify a subset of vertices where each vertex of a graph must be dominated by at least half of its neighbors. To solve these problems, we propose a two-stage hybrid local search algorithm. In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. Moreover, we introduce information content strategy-based neighborhood structure and tolerance-based features to evolve high-quality and diverse solutions. For the second stage, we propose a gain-based deterministic local search algorithm as an exploitation procedure. It navigates feasible neighborhood areas to improve the solution quality. We conducted extensive analysis to evaluate the impact of the proposed components. The proposed algorithm produced very good results and generalized well overall instances of both MDS and MPIDS. Compared to the literature, the proposed algorithm outperformed other algorithms in most of the tested instances. Â© 2022 Elsevier Ltd
format	Article
author	Abed, S.A. Rais, H.M. Watada, J. Sabar, N.R.
spellingShingle	Abed, S.A. Rais, H.M. Watada, J. Sabar, N.R. A hybrid local search algorithm for minimum dominating set problems
author_facet	Abed, S.A. Rais, H.M. Watada, J. Sabar, N.R.
author_sort	Abed, S.A.
title	A hybrid local search algorithm for minimum dominating set problems
title_short	A hybrid local search algorithm for minimum dominating set problems
title_full	A hybrid local search algorithm for minimum dominating set problems
title_fullStr	A hybrid local search algorithm for minimum dominating set problems
title_full_unstemmed	A hybrid local search algorithm for minimum dominating set problems
title_sort	hybrid local search algorithm for minimum dominating set problems
publisher	Elsevier Ltd
publishDate	2022
url	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132527008&doi=10.1016%2fj.engappai.2022.105053&partnerID=40&md5=3039d1f8630093a54635c16e891d1c95 http://eprints.utp.edu.my/33322/
_version_	1739833206082895872
score	13.244414

A hybrid local search algorithm for minimum dominating set problems

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