We present a new primal-dual algorithm for convex quadratic multicriteria optimization. The algorithm is able to adaptively refine the approximation to the set of efficient points by way of a warm-start interior-point scalarization approach. Results of this algorithm when applied on a three-criteria real-world power plant optimization problem are reported, thereby illustrating the feasibility of this approach when used in practice.
Citation
Preprint 2006/34, School of Mathematics, The University of Birmingham, Edbagston, Birmingham B15 2TT, UK.
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View An Adaptive Primal-Dual Warm-Start Technique for Quadratic Multiobjective Optimization