Binary social group optimization algorithm for solving 0-1 knapsack problem

In this paper, we propose the binary version of the Social Group Optimization (BSGO) algorithm for solving the 0-1 knapsack problem. The standard Social Group Optimization (SGO) is used for continuous optimization problems. So a transformation function is used to convert the continuous valu...

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Autores principales: Anima Naik, Pradeep Kumar Chokkalingam
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Lenguaje:EN
Publicado: Growing Science 2022
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Acceso en línea:https://doaj.org/article/c5cdf5c9e85b4c38b5546c05fefcf53c
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spelling oai:doaj.org-article:c5cdf5c9e85b4c38b5546c05fefcf53c2021-11-12T06:26:20ZBinary social group optimization algorithm for solving 0-1 knapsack problem1929-58041929-581210.5267/j.dsl.2021.8.004https://doaj.org/article/c5cdf5c9e85b4c38b5546c05fefcf53c2022-01-01T00:00:00Zhttp://www.growingscience.com/dsl/Vol11/dsl_2021_32.pdfhttps://doaj.org/toc/1929-5804https://doaj.org/toc/1929-5812 In this paper, we propose the binary version of the Social Group Optimization (BSGO) algorithm for solving the 0-1 knapsack problem. The standard Social Group Optimization (SGO) is used for continuous optimization problems. So a transformation function is used to convert the continuous values generated from SGO into binary ones. The experiments are carried out using both low-dimensional and high-dimensional knapsack problems. The results obtained by the BSGO algorithm are compared with other binary optimization algorithms. Experimental results reveal the superiority of the BSGO algorithm in achieving a high quality of solutions over different algorithms and prove that it is one of the best finding algorithms especially in high-dimensional cases.Anima NaikPradeep Kumar ChokkalingamGrowing SciencearticleAnalysisQA299.6-433Business mathematics. Commercial arithmetic. Including tables, etc.HF5691-5716ENDecision Science Letters, Vol 11, Iss 1, Pp 55-72 (2022)
institution DOAJ
collection DOAJ
language EN
topic Analysis
QA299.6-433
Business mathematics. Commercial arithmetic. Including tables, etc.
HF5691-5716
spellingShingle Analysis
QA299.6-433
Business mathematics. Commercial arithmetic. Including tables, etc.
HF5691-5716
Anima Naik
Pradeep Kumar Chokkalingam
Binary social group optimization algorithm for solving 0-1 knapsack problem
description In this paper, we propose the binary version of the Social Group Optimization (BSGO) algorithm for solving the 0-1 knapsack problem. The standard Social Group Optimization (SGO) is used for continuous optimization problems. So a transformation function is used to convert the continuous values generated from SGO into binary ones. The experiments are carried out using both low-dimensional and high-dimensional knapsack problems. The results obtained by the BSGO algorithm are compared with other binary optimization algorithms. Experimental results reveal the superiority of the BSGO algorithm in achieving a high quality of solutions over different algorithms and prove that it is one of the best finding algorithms especially in high-dimensional cases.
format article
author Anima Naik
Pradeep Kumar Chokkalingam
author_facet Anima Naik
Pradeep Kumar Chokkalingam
author_sort Anima Naik
title Binary social group optimization algorithm for solving 0-1 knapsack problem
title_short Binary social group optimization algorithm for solving 0-1 knapsack problem
title_full Binary social group optimization algorithm for solving 0-1 knapsack problem
title_fullStr Binary social group optimization algorithm for solving 0-1 knapsack problem
title_full_unstemmed Binary social group optimization algorithm for solving 0-1 knapsack problem
title_sort binary social group optimization algorithm for solving 0-1 knapsack problem
publisher Growing Science
publishDate 2022
url https://doaj.org/article/c5cdf5c9e85b4c38b5546c05fefcf53c
work_keys_str_mv AT animanaik binarysocialgroupoptimizationalgorithmforsolving01knapsackproblem
AT pradeepkumarchokkalingam binarysocialgroupoptimizationalgorithmforsolving01knapsackproblem
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