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A Finite Algorithm for Globally Optimizing a Class of Rank-Two Reverse Convex Programs

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Abstract

In this paper, we propose an algorithm for solving a linear program with an additional rank-two reverse convex constraint. Unlike the existing methods which generate approximately optimal solutions, the algorithm provides a rigorous optimal solution to this nonconvex problem by a finite number of dual pivot operations. Computational results indicate that the algorithm is practical and can solve fairly large scale problems.

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Authors and Affiliations

  1. Institute of Information Sciences and Electronics, University of Tsukuba, Tsukuba, Ibaraki, 305, Japan (email

    Takahito Kuno

  2. Institute of Policy and Planning Sciences, University of Tsukuba, Tsukuba, Ibaraki, 305, Japan (email

    Yoshitsugu Yamamoto

Authors
  1. Takahito Kuno
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  2. Yoshitsugu Yamamoto
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Kuno, T., Yamamoto, Y. A Finite Algorithm for Globally Optimizing a Class of Rank-Two Reverse Convex Programs. Journal of Global Optimization 12, 247–265 (1998). https://doi.org/10.1023/A:1008216024699

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  • DOI: https://doi.org/10.1023/A:1008216024699

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