Abstract
In this paper, second order differential evolution (SODE) algorithm is considered to solve the constrained optimization problems. After offspring are generated by the second order differential evolution, the ε constrained method is chosen for selection in this paper. In order to show that second order differential vector is better than differential vector in solving constrained optimization problems, differential evolution (DE) with the ε constrained method is used for performance comparison. The experiments on 12 test functions from IEEE CEC 2006 demonstrate that second order differential evolution shows better or at least competitive performance against DE when dealing with constrained optimization problems.
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Acknowledgments
This research is supported by National Natural Science Foundation of China (71772060, 61873040, 61375066). We will express our awfully thanks to the Swarm Intelligence Research Team of BeiYou University.
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Zhao, X., Liu, J., Hao, J., Chen, J., Zuo, X. (2019). Second Order Differential Evolution for Constrained Optimization. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11655. Springer, Cham. https://doi.org/10.1007/978-3-030-26369-0_36
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DOI: https://doi.org/10.1007/978-3-030-26369-0_36
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