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Global Sufficient Conditions for Nonconvex Cubic Minimization Problem with Box Constraints

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Advances in Global Optimization

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 95))

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Abstract

In this paper, we focus on deriving some sufficient conditions for global solutions to cubic minimization problems with box constraints. Our main tool is an extension of the global subdifferential, L-normal cone approach, developed by Jeyakumar et al. (J. Glob. Optim., 2007; Math. Program. Ser. A 110, 2007), and underestimator functions. By applying these tools to characteristic global solutions, we provide some sufficient conditions for cubic programming problem with box constraints. An example is given to demonstrate that the sufficient conditions can be used effectively for identifying global minimizers of certain cubic minimization problems with box constraints.

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Acknowledgements

This research was supported by NSFC (11271243), Innovation Program of Shanghai Municipal Education Commission (12ZZ071), and Shanghai Pujiang Program (11PJC059).

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Correspondence to Yanjun Wang .

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Wang, Y., Liang, Z., Shen, L. (2015). Global Sufficient Conditions for Nonconvex Cubic Minimization Problem with Box Constraints. 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_4

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