The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance

Metaheuristics (MH) aptitude to move past local optimums makes them an attractive technique to approach complex computational problems, such as the Travelling Salesman Problem (TSP), but there is lack of information on the parameterization procedure and the appropriate parameters to improve MHs’ per...

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Main Authors: A. S. Santos, A. M. Madureira, M. L. R. Varela
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2018/8072621
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spelling doaj-dd8cdcc497474d44b203a4dbc2cc50e62020-11-24T23:11:33ZengHindawi LimitedJournal of Mathematics2314-46292314-47852018-01-01201810.1155/2018/80726218072621The Influence of Problem Specific Neighborhood Structures in Metaheuristics PerformanceA. S. Santos0A. M. Madureira1M. L. R. Varela2Interdisciplinary Studies Research Center (ISRC), School of Engineering, Polytechnic Institute of Porto (ISEP/IPP), PortugalInterdisciplinary Studies Research Center (ISRC), School of Engineering, Polytechnic Institute of Porto (ISEP/IPP), PortugalDepartment of Production and Systems, University of Minho, PortugalMetaheuristics (MH) aptitude to move past local optimums makes them an attractive technique to approach complex computational problems, such as the Travelling Salesman Problem (TSP), but there is lack of information on the parameterization procedure and the appropriate parameters to improve MHs’ performance. In this paper the parameterization procedure of Simulated Annealing (SA) and Discrete Artificial Bee Colony (DABC) is addressed, with a focus on the Neighborhood Structure (NS). Numerous NS have been proposed for specific problems, which seem to indicate that the NS is a special parameter, whose optimization is independent of other parameters. The performance of eight NS was examined with SA and DABC under two optimization constraints, regarding computational time variation, to determine if there is one appropriate NS for the TSP problem, independent of the rest of the parameters of the optimization procedure. The computational study carried out for comparing the evaluation of the NS, including a statistical analysis, demonstrated a nonproportional increase in the performance of DABC with some NS. For SA the improvement of the solutions appeared to be more uniform with an almost nonexistent variance in improvement.http://dx.doi.org/10.1155/2018/8072621
collection DOAJ
language English
format Article
sources DOAJ
author A. S. Santos
A. M. Madureira
M. L. R. Varela
spellingShingle A. S. Santos
A. M. Madureira
M. L. R. Varela
The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
Journal of Mathematics
author_facet A. S. Santos
A. M. Madureira
M. L. R. Varela
author_sort A. S. Santos
title The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
title_short The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
title_full The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
title_fullStr The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
title_full_unstemmed The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
title_sort influence of problem specific neighborhood structures in metaheuristics performance
publisher Hindawi Limited
series Journal of Mathematics
issn 2314-4629
2314-4785
publishDate 2018-01-01
description Metaheuristics (MH) aptitude to move past local optimums makes them an attractive technique to approach complex computational problems, such as the Travelling Salesman Problem (TSP), but there is lack of information on the parameterization procedure and the appropriate parameters to improve MHs’ performance. In this paper the parameterization procedure of Simulated Annealing (SA) and Discrete Artificial Bee Colony (DABC) is addressed, with a focus on the Neighborhood Structure (NS). Numerous NS have been proposed for specific problems, which seem to indicate that the NS is a special parameter, whose optimization is independent of other parameters. The performance of eight NS was examined with SA and DABC under two optimization constraints, regarding computational time variation, to determine if there is one appropriate NS for the TSP problem, independent of the rest of the parameters of the optimization procedure. The computational study carried out for comparing the evaluation of the NS, including a statistical analysis, demonstrated a nonproportional increase in the performance of DABC with some NS. For SA the improvement of the solutions appeared to be more uniform with an almost nonexistent variance in improvement.
url http://dx.doi.org/10.1155/2018/8072621
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