Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions

The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to va...

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Detalles Bibliográficos
Autores principales: Harita, Maria, Wong, Alvaro, Rexachs del Rosario, Dolores, Luque Fadón, Emilio
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2020
Materias:
Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/104772
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-104772
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
spellingShingle Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
Harita, Maria
Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
topic_facet Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
description The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality.
format Objeto de conferencia
Objeto de conferencia
author Harita, Maria
Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author_facet Harita, Maria
Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author_sort Harita, Maria
title Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_short Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_full Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_fullStr Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_full_unstemmed Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_sort evaluation of the quality of the ”montecarlo plus k-means” heuristics using benchmark functions
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/104772
work_keys_str_mv AT haritamaria evaluationofthequalityofthemontecarlopluskmeansheuristicsusingbenchmarkfunctions
AT wongalvaro evaluationofthequalityofthemontecarlopluskmeansheuristicsusingbenchmarkfunctions
AT rexachsdelrosariodolores evaluationofthequalityofthemontecarlopluskmeansheuristicsusingbenchmarkfunctions
AT luquefadonemilio evaluationofthequalityofthemontecarlopluskmeansheuristicsusingbenchmarkfunctions
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