Abstract
In this work, constrained minimax problems are studied. By use of proposing a differentially auxiliary function and providing explicit search direction with the aid idea of generalized gradient project technique, a new algorithm with Armjio non-exact linear search is presented and its global convergence is obtained under arbitrary initial point condition.
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Acknowledgment
This work was supported in part by the National Natural Science Foundation (11361018), the Natural Science Foundation of Guangxi Province (2014GXN SFFA118001), the Key Program for Science and Technology in Henan Education Institution (15B110008, 17A110030) and Huarui College Science Foundation (2014qn35) of China.
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Zhang, C., Sun, L., Zhu, Z. (2016). Generalized Project Gradient Algorithm for Solving Constrained Minimax Problems. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_17
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DOI: https://doi.org/10.1007/978-981-10-3614-9_17
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