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

Anima Naik | Zendy; Pradeep Kumar Chokkalingam | Zendy

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

Author(s) -

Anima Naik,

Pradeep Kumar Chokkalingam

Publication year - 2021

Publication title -

decision science letters

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.384

H-Index - 18

eISSN - 1929-5804

pISSN - 1929-5812

DOI - 10.5267/j.dsl.2021.8.004

Subject(s) - knapsack problem , continuous knapsack problem , binary number , algorithm , mathematical optimization , optimization problem , group (periodic table) , mathematics , transformation (genetics) , continuous optimization , polynomial time approximation scheme , computer science , multi swarm optimization , chemistry , biochemistry , arithmetic , organic chemistry , gene

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.

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