Abstract
In this paper, we propose a parallel decomposition algorithm for solving a class of convex optimization problems, which is broad enough to contain ordinary convex programming problems with a strongly convex objective function. The algorithm is a variant of the trust region method applied to the Fenchel dual of the given problem. We prove global convergence of the algorithm and report some computational experience with the proposed algorithm on the Connection Machine Model CM-5.
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Fukushima, M., Haddou, M., Van Nguyen, H. et al. A parallel descent algorithm for convex programming. Comput Optim Applic 5, 5–37 (1996). https://doi.org/10.1007/BF00429749
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DOI: https://doi.org/10.1007/BF00429749