A Metaheuristic Optimization Algorithm Inspired by the Effect of Sunlight on the Leaf Germination

Farzaneh Hosseini and Marjan Kaedi
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Farzaneh Hosseini: Islamic Azad University, Qeshm International Branch, Qeshm, Iran
Marjan Kaedi: Department of Computer Engineering, University of Isfahan, Isfahan, Iran

International Journal of Applied Metaheuristic Computing (IJAMC), 2018, vol. 9, issue 1, 40-48

Abstract: This paper develops a nature-inspired metaheuristic algorithm named sun and leaf optimization (SLO) which is inspired by the effect of sunlight on the leaves germination. In SLO, candidate solutions in the state space are considered as leaves grown on a tree, and high-quality solutions are considered as greener leaves germinated in the direction of sunlight. On a tree, usually greener leaves are found closed to each other, because such area is probably exposed more to the sun and hence it is suitable for hosting other greener leaves. Inspired by this phenomenon, in SLO, during the search, the authors take the existence of high quality solutions as a sign of promising areas for finding optimum; thus, they generate more candidate solutions near the higher quality solutions to search those areas more painstakingly. Wind effect is imitated to escape the local optima. The evaluation results demonstrate the high performance of proposed algorithm.

Date: 2018
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