Abstract
Metaheuristics have been proposed as an alternative to mathematical optimization methods to address non convex problems involving large search spaces. Within this context a new promising metaheuristic inspired from earth atmosphere phenomena and termed as Wind Driven Optimization (WDO) has been developed by Bayraktar. WDO has been successfully applied to solve continuous optimization problems. However it requires tuning several parameters and it may lead to premature convergence. In this paper the basic WDO is modified in a way to improve the search capabilities of the algorithm and to reduce the number of tunable parameters. In the proposed variant of WDO, the original model equation is modified by introducing a pressure based term to replace the rank based term. Furthermore, the value of the gravitational term is automatically and adaptively set. The performance of the proposed modified WDO has been assessed using several benchmarks in numerical optimization. The obtained results show that the modified WDO outperforms the original WDO in most test problems from both accuracy and robustness.
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Boulesnane, A., Meshoul, S. (2015). A Modified Wind Driven Optimization Model for Global Continuous Optimization. In: Onieva, E., Santos, I., Osaba, E., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2015. Lecture Notes in Computer Science(), vol 9121. Springer, Cham. https://doi.org/10.1007/978-3-319-19644-2_25
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DOI: https://doi.org/10.1007/978-3-319-19644-2_25
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