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Global Approximation of Local Optimality: Nonsubmodular Optimization

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Abstract

In the study of information technology, one of the important efforts is made on dealing with nonsubmodular optimizations since there are many such problems raised in various areas of computer and information science. Usually, nonsubmodular optimization problems are NP-hard. Therefore, design and analysis of approximation algorithms are important tasks in the study of nonsubmodular optimizations. However, the traditional methods do not work well. Therefore, a new method, the global approximation of local optimality, is proposed recently. In this paper, we give an extensive study for this new methodology.

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Authors and Affiliations

  1. Department of Computer Science, University of Texas at Dallas, Richardson, TX, 75080, USA

    Wei-Li Wu & Ding-Zhu Du

  2. College of Mathematics and Computer Science, Zhejiang Normal University, **hua, 321004, Zhejiang, China

    Zhao Zhang

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  1. Wei-Li Wu
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  2. Zhao Zhang
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  3. Ding-Zhu Du
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All authors contributed equally to this work.

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Correspondence to Zhao Zhang or Ding-Zhu Du.

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This research is supported in part by the National Natural Science Foundation of China (No. U20A2068), Zhejiang Provincial Natural Science Foundation of China (No. LD19A010001), and Natural Science Foundation of USA (No. 1907472).

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Wu, WL., Zhang, Z. & Du, DZ. Global Approximation of Local Optimality: Nonsubmodular Optimization. J. Oper. Res. Soc. China (2023). https://doi.org/10.1007/s40305-023-00475-3

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  • DOI: https://doi.org/10.1007/s40305-023-00475-3

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