Abstract
Spider Monkey Optimization (SMO) algorithm is recently developed optimiser that is stimulated by the extraordinary social activities of spider monkeys known as fission–fusion social structure. The SMO is developed to find the solution of difficult optimization problems in real world, which are difficult to solve by the available deterministic strategies. Here, three modifications in SMO algorithm are selected for the purpose of comparison, namely, exponential SMO, chaotic SMO and sigmoidal SMO. These modifications suggested new strategies for selecting perturbation rate in local leader and local leader decision phase. These strategies replaced linear approach of perturbation by nonlinear functions. The proposed strategies are tested over a set of benchmark functions.
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Sharma, B., Sharma, V.K., Kumar, S. (2020). Comparative Analysis of Selected Variant of Spider Monkey Optimization Algorithm. In: Sharma, H., Govindan, K., Poonia, R., Kumar, S., El-Medany, W. (eds) Advances in Computing and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0222-4_33
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DOI: https://doi.org/10.1007/978-981-15-0222-4_33
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