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Absolute value equation solution via concave minimization

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Abstract

The NP-hard absolute value equation (AVE) Ax − |x| = b where \(A\in R^{n\times n}\) and \(b\in R^n\) is solved by a succession of linear programs. The linear programs arise from a reformulation of the AVE as the minimization of a piecewise-linear concave function on a polyhedral set and solving the latter by successive linearization. A simple MATLAB implementation of the successive linearization algorithm solved 100 consecutively generated 1,000-dimensional random instances of the AVE with only five violated equations out of a total of 100,000 equations.

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Authors and Affiliations

  1. Computer Sciences Department, University of Wisconsin, Madison, WI, 53706, USA

    O. L. Mangasarian

  2. Department of Mathematics, University of California at San Diego, La Jolla, CA, 92093, USA

    O. L. Mangasarian

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  1. O. L. Mangasarian
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Correspondence to O. L. Mangasarian.

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Mangasarian, O.L. Absolute value equation solution via concave minimization. Optimization Letters 1, 3–8 (2007). https://doi.org/10.1007/s11590-006-0005-6

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  • DOI: https://doi.org/10.1007/s11590-006-0005-6

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