MFO has excellent performance in solving optimization problems and has strong ability in solving power optimization combination. Algorithms, 11(4), 47. The effectiveness of CMFO algorithm has been verified by 4 benchmark problems. In the second approach, the crossover operator is used in addition to the transfer functions to replace the average operator and enhance the exploratory behavior of the algorithm. Novel energy management technique for hybrid electric vehicle via interconnection and damping assignment passivity based control. Ebrahim, M. A., Ali, A. M., & Hassan, M. M. (2017). In 2018 Twentieth International Middle East Power Systems Conference (MEPCON) (pp. to your librarian.If you already have i-manager's user account: Login above and proceed to purchase the article.New Users: Please register, then proceed to purchase the article. It can beconcluded that SMWOA can avoid local minimum and has a good convergence rate forThe SMWOA failed to show the best standard deviation on In summary, the experimental results show that SMWOAcompetitive and superior to other well-known algorithms (Figs. MPPT algorithm for thermoelectric generators based on parabolic extrapolation. Different scenarios of solar irradiance, temperature variation, and load fluctuations were used to check the feasibility of the proposed optimizer. (2011). (Eds. International Journal of Renewable Energy Development, 5(3), 225-232.[38].
Chen, Y., Vepa, R., & Shaheed, M. H. (2018). Pandiarajan, N., & Muthu, R. (2011, January). Results show that the proposed model can significantly improve the performance metrics.This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. (2017). Wind-driven optimization technique for estimation of solar photovoltaic parameters. The SCA algorithm obtains a smooth shape for the airfoil with a very low drag, which demonstrates that this algorithm can highly be effective in solving real problems with constrained and unknown search spaces. Therefore, when solving the optimization problem, it may rapidD.-S. Huang et al. To evaluate the performance of SMWOA,functions and compared them with the other seven most advanced meta-heurmost test cases and that SMWOA is a feasible and quiteSMWOA performs well in unknown and challenging search space.An Enhanced Whale Optimization Algorithm with Simplex MethodGrant No. The results are deeply validated in comparison with eight recent and well-regarded algorithms qualitatively and quantitatively.
A. ): ICIC 2019, LNCS 11643, pp. Solar Energy, 171, 593-603.[8]. IEEE Transactions on Circuits and Systems II: Express Briefs, 66(2), 257-261.[30]. Note that the source codes of the SCA algorithm are publicly available at http://www.alimirjalili.com/SCA.html.Constrained optimization problems are very important as they are encountered in many science and engineering applications.
Comput.
Villalva, M. G., Gazoli, J. R., & Ruppert Filho, E. (2009, September). The experimental results confirms that the proposed system can achieve to remarkable results in terms of accuracy, precision, and recall. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Global MPPT based on flower pollination and differential evolution algorithms to mitigate partial shading in building integrated PV system.
All rights reserved.This paper proposes an enhanced whale optimization algorithm with]. IET Electric Power Applications, 11(8), 1432-1440.[58]. 374approach to solve structural optimization problems. Although numerous effort estimation models have been proposed during the last decade, accuracy level is not satisfying enough. trajectory is helpful for increasing the diversity of the population against premature convergence and enhancing the capability of jumping out of local optimal optima. Theexperimental results show that the SMWOA algorithm has better performancethan other meta-heuristic optimization algorithms in low and high dimensions.In recent years, a great many nature-inspired meta-heuristic algorithms have beendeveloped and applied to many optimization problems [have become popular, with the main inspiration comingtralized, self-organizing, collaborative search agent systems [traditional precise algorithm, the stochastic optimiwith a large number of decision variables but also has strong competitiveness and closeto the optimal results. J. IEEE Power and Energy Technology Systems Journal, 5(1), 11-17.[37].
algorithm for function optimization problems. IEEE Transactions on Sustainable Energy, 8(3), 1204-1214.[39]. The LWOA is further compared with other well-known nature-inspired algorithms on 23 benchmarks and solving infinite impulse response (IIR) model identification. Soft Comput. Automatic voltage generation control for two area power system based on particle swarm optimization. Bijukumar, B., Raam, A. G. K., Ganesan, S. I., Nagamani, C., & Reddy, M. J.
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