A survey of adaptive large neighborhood search algorithms and applications

A survey of adaptive large neighborhood search algorithms and applications

This article provides a survey on the highly popular metaheuristic framework, the adaptive large neighborhood search (ALNS). The basic concepts of ALNS are discussed in this paper. Based on a simple taxonomy, the analysis of publication intensity, application areas, and the variant of ALNS features...

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Main Authors: Mara, Setyo Tri Windras, Norcahyo, Rahmadi, Jodiawan, Panca, Lusiantoro, Luluk, Rifai, Achmad Pratama
Format: Article PeerReviewed
Language:English
Published: Elsevier 2022
Subjects:
Engineering
Mechanical Engineering
Online Access:https://repository.ugm.ac.id/278606/1/Mara_TK.pdf
https://repository.ugm.ac.id/278606/
https://www.elsevier.com/locate/cor
https://doi.org/10.1016/j.cor.2022.105903
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Institution: Universitas Gadjah Mada
Language: English
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spelling id-ugm-repo.2786062023-11-02T02:08:24Z https://repository.ugm.ac.id/278606/ A survey of adaptive large neighborhood search algorithms and applications Mara, Setyo Tri Windras Norcahyo, Rahmadi Jodiawan, Panca Lusiantoro, Luluk Rifai, Achmad Pratama Engineering Mechanical Engineering This article provides a survey on the highly popular metaheuristic framework, the adaptive large neighborhood search (ALNS). The basic concepts of ALNS are discussed in this paper. Based on a simple taxonomy, the analysis of publication intensity, application areas, and the variant of ALNS features are executed on 252 scientific publications to synthesize the state-of-the-art of ALNS research. Finally, some discussions on the future research of ALNS are provided Elsevier 2022-06-09 Article PeerReviewed application/pdf en https://repository.ugm.ac.id/278606/1/Mara_TK.pdf Mara, Setyo Tri Windras and Norcahyo, Rahmadi and Jodiawan, Panca and Lusiantoro, Luluk and Rifai, Achmad Pratama (2022) A survey of adaptive large neighborhood search algorithms and applications. Computers and Operations Research, 146 (2022). pp. 1-19. ISSN 1873-765X https://www.elsevier.com/locate/cor https://doi.org/10.1016/j.cor.2022.105903
institution Universitas Gadjah Mada
building UGM Library
continent Asia
country Indonesia
Indonesia
content_provider UGM Library
collection Repository Civitas UGM
language English
topic Engineering
Mechanical Engineering
spellingShingle Engineering
Mechanical Engineering
Mara, Setyo Tri Windras
Norcahyo, Rahmadi
Jodiawan, Panca
Lusiantoro, Luluk
Rifai, Achmad Pratama
A survey of adaptive large neighborhood search algorithms and applications
description This article provides a survey on the highly popular metaheuristic framework, the adaptive large neighborhood search (ALNS). The basic concepts of ALNS are discussed in this paper. Based on a simple taxonomy, the analysis of publication intensity, application areas, and the variant of ALNS features are executed on 252 scientific publications to synthesize the state-of-the-art of ALNS research. Finally, some discussions on the future research of ALNS are provided
format Article
PeerReviewed
author Mara, Setyo Tri Windras
Norcahyo, Rahmadi
Jodiawan, Panca
Lusiantoro, Luluk
Rifai, Achmad Pratama
author_facet Mara, Setyo Tri Windras
Norcahyo, Rahmadi
Jodiawan, Panca
Lusiantoro, Luluk
Rifai, Achmad Pratama
author_sort Mara, Setyo Tri Windras
title A survey of adaptive large neighborhood search algorithms and applications
title_short A survey of adaptive large neighborhood search algorithms and applications
title_full A survey of adaptive large neighborhood search algorithms and applications
title_fullStr A survey of adaptive large neighborhood search algorithms and applications
title_full_unstemmed A survey of adaptive large neighborhood search algorithms and applications
title_sort survey of adaptive large neighborhood search algorithms and applications
publisher Elsevier
publishDate 2022
url https://repository.ugm.ac.id/278606/1/Mara_TK.pdf
https://repository.ugm.ac.id/278606/
https://www.elsevier.com/locate/cor
https://doi.org/10.1016/j.cor.2022.105903
_version_ 1781794669483524096

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