Summary.
A quadratic programming method is given for minimizing a sum of piecewise linear functions and a proximal quadratic term, subject to simple bounds on variables. It may be used for search direction finding in nondifferentiable optimization algorithms. An efficient implementation is described that updates a Cholesky factorization of active constraints and provides good accuracy via iterative refinement. Numerical experience is reported for some large problems.
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Received March 29, 1993 / Revised version received December 18, 1993
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Kiwiel, K. A Cholesky dual method for proximal piecewise linear programming . Numer. Math. 68, 325–340 (1994). https://doi.org/10.1007/s002110050065
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DOI: https://doi.org/10.1007/s002110050065