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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Growing Science
2022
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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) |
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Analysis QA299.6-433 Business mathematics. Commercial arithmetic. Including tables, etc. HF5691-5716 |
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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 |
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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 |
_version_ |
1718431195478360064 |