Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem

Search trajectory networks (STNs) were proposed as a tool to analyze the behavior of metaheuristics in relation to their exploration ability and the search space regions they traverse. The technique derives from the study of fitness landscapes using local optima networks (LONs). STNs are related to...

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Autores principales:	Valentina Narvaez-Teran, Gabriela Ochoa, Eduardo Rodriguez-Tello
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Search trajectory networks cyclic bandwidth sum problem hyperheuristics memetic algorithms hybridization Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/7f885e02c0824bf4bbb7171dc4039212
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id	oai:doaj.org-article:7f885e02c0824bf4bbb7171dc4039212
record_format	dspace
spelling	oai:doaj.org-article:7f885e02c0824bf4bbb7171dc40392122021-11-17T00:01:18ZSearch Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem2169-353610.1109/ACCESS.2021.3126015https://doaj.org/article/7f885e02c0824bf4bbb7171dc40392122021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9605670/https://doaj.org/toc/2169-3536Search trajectory networks (STNs) were proposed as a tool to analyze the behavior of metaheuristics in relation to their exploration ability and the search space regions they traverse. The technique derives from the study of fitness landscapes using local optima networks (LONs). STNs are related to LONs in that both are built as graphs, modelling the transitions among solutions or group of solutions in the search space. The key difference is that STN nodes can represent solutions or groups of solutions that are not necessarily locally optimal. This work presents an STN-based study for a particular combinatorial optimization problem, the cyclic bandwidth sum minimization. STNs were employed to analyze the two leading algorithms for this problem: a memetic algorithm and a hyperheuristic memetic algorithm. We also propose a novel grouping method for STNs that can be generally applied to both continuous and combinatorial spaces.Valentina Narvaez-TeranGabriela OchoaEduardo Rodriguez-TelloIEEEarticleSearch trajectory networkscyclic bandwidth sum problemhyperheuristicsmemetic algorithmshybridizationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 151266-151277 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Search trajectory networks cyclic bandwidth sum problem hyperheuristics memetic algorithms hybridization Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Search trajectory networks cyclic bandwidth sum problem hyperheuristics memetic algorithms hybridization Electrical engineering. Electronics. Nuclear engineering TK1-9971 Valentina Narvaez-Teran Gabriela Ochoa Eduardo Rodriguez-Tello Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
description	Search trajectory networks (STNs) were proposed as a tool to analyze the behavior of metaheuristics in relation to their exploration ability and the search space regions they traverse. The technique derives from the study of fitness landscapes using local optima networks (LONs). STNs are related to LONs in that both are built as graphs, modelling the transitions among solutions or group of solutions in the search space. The key difference is that STN nodes can represent solutions or groups of solutions that are not necessarily locally optimal. This work presents an STN-based study for a particular combinatorial optimization problem, the cyclic bandwidth sum minimization. STNs were employed to analyze the two leading algorithms for this problem: a memetic algorithm and a hyperheuristic memetic algorithm. We also propose a novel grouping method for STNs that can be generally applied to both continuous and combinatorial spaces.
format	article
author	Valentina Narvaez-Teran Gabriela Ochoa Eduardo Rodriguez-Tello
author_facet	Valentina Narvaez-Teran Gabriela Ochoa Eduardo Rodriguez-Tello
author_sort	Valentina Narvaez-Teran
title	Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
title_short	Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
title_full	Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
title_fullStr	Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
title_full_unstemmed	Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem
title_sort	search trajectory networks applied to the cyclic bandwidth sum problem
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/7f885e02c0824bf4bbb7171dc4039212
work_keys_str_mv	AT valentinanarvaezteran searchtrajectorynetworksappliedtothecyclicbandwidthsumproblem AT gabrielaochoa searchtrajectorynetworksappliedtothecyclicbandwidthsumproblem AT eduardorodrigueztello searchtrajectorynetworksappliedtothecyclicbandwidthsumproblem
_version_	1718426058584227840

Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem

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