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The oyster collection algorithms

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Abstract

This article focuses on the development of metaheuristic algorithms based on the search process and collection of the oysters (living or non-living) from the sea bed in the day time. In the coastal belt, during tides, oysters are pushed by the water waves and gathered in specific places on the sea bed. For living oysters, they are generally found in the cold-water region, but for non-living shells, they can be found anywhere in the sea bed, depending on the blow of the wind and the path of the water wave. Since oysters have many economic values (because indoor decoration, ornaments and gift packs etc. are made using these sea shells), people from coastal zones usually collect them and plan for one of the best jobs/ trades in their social life. Inspiring from the nature of the collection procedure of the shells, we construct mathematical functions of the search path along which it can be available more. Utilizing this procedure into the field of optimization, we have found some noble results of a benchmark problem. Basically, we fit an appropriate test function for a benchmark problem, then some numeric experimental results are computed via oyster collection algorithms. A comparative study has also been made to validate the proposed approach. Moreover, considering the normality of the data, we have studied confidence intervals and analyzed statistically for the global acceptance of the method. It is also seen that the root mean square error (RMSE) for our proposed algorithms is 0.004007 and that for the other existing algorithms it becomes 0.007015. This gives the excellence success rate in the field of optimization with respect to others all the time. Indeed, the graphical illustrations show the efficacy of the proposed algorithms and, finally, a conclusion is made about keeping some scope for future works.

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Acknowledgements

The authors have acknowledged the Editor in Chief for the consideration of our article and the annonimous reviewers for their valuable suggestions to improve the quality of our article.

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Authors and Affiliations

  1. Department of Mathematics, Midnapore College (Autonomous), Midnapore, WB, 721101, India

    Sujit Kumar De

  2. Department of Mathematics, Kharagpur College, Kharagpur, WB, 721305, India

    Kousik Bhattacharya

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  1. Sujit Kumar De
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Contributions

S. K. De gives the Concept, Original draft writing, Data generation, Algorithm use, Graphical illustrations and Reviewing K. Bhattacharya did the Software use, Algorithm code generation, Drawing graphs, Data generation and Reviewing.

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Correspondence to Sujit Kumar De.

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De, S.K., Bhattacharya, K. The oyster collection algorithms. Evol. Intel. (2024). https://doi.org/10.1007/s12065-024-00967-y

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