Abstract
The aim of this paper is to propose a global algorithm model for continuous constrained nonlinear programming based on a new simple and exact penalty function. Under weak assumptions, we show that the optimizer obtained by the algorithm is converged to the global minimizer of the original problem.
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Acknowledgements
This research was partially supported by the National Natural Science Foundation of China (10571116 and 51075421), and supported by Science Foundation of Zhejiang Sci-Tech University (ZSTU) under Grant No. 1206830-Y.
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Zheng, F., Zhang, L. (2015). Constrained Global Optimization Using a New Exact Penalty Function. In: Gao, D., Ruan, N., Xing, W. (eds) Advances in Global Optimization. Springer Proceedings in Mathematics & Statistics, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-319-08377-3_8
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DOI: https://doi.org/10.1007/978-3-319-08377-3_8
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