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Convexification and Monotone Optimization

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Continuous Optimization

Part of the book series: Applied Optimization ((APOP,volume 99))

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Summary

Monotone maximization is a global optimization problem that maximizes an increasing function subject to increasing constraints. Due to the often existence of multiple local optimal solutions, finding a global optimal solution of such a problem is computationally difficult. In this survey paper, we summarize global solution methods for the monotone optimization problem. In particular, we propose a unified framework for the recent progress on convexification methods for the monotone optimization problem. Suggestions for further research are also presented.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Shanghai University, Shanghai, 200444, P.R. China

    Xiaoling Sun & Jianling Li

  2. College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi, 530004, P.R. China

    Jianling Li

  3. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, P.R. China

    Duan Li

Authors
  1. Xiaoling Sun
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  2. Jianling Li
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  3. Duan Li
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Editor information

Editors and Affiliations

  1. University of New South Wales, Sydney, Australia

    Vaithilingam Jeyakumar

  2. University of Ballarat, Ballarat, Australia

    Alexander Rubinov

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© 2005 Springer Science+Business Media, Inc.

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Sun, X., Li, J., Li, D. (2005). Convexification and Monotone Optimization. In: Jeyakumar, V., Rubinov, A. (eds) Continuous Optimization. Applied Optimization, vol 99. Springer, Boston, MA. https://doi.org/10.1007/0-387-26771-9_9

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