Global Optimality Conditions for Classes of Non-convex Multi-objective Quadratic Optimization Problems

V. Jeyakumar (), G. M. Lee () and G. Li ()
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V. Jeyakumar: University of New South Wales
G. M. Lee: Pukyong National University
G. Li: University of New South Wales

A chapter in Variational Analysis and Generalized Differentiation in Optimization and Control, 2010, pp 177-186 from Springer

Abstract: Abstract We present necessary and sufficient conditions for identifying global weak minimizers of non-convex multi-objective quadratic optimization problems. We derive these results by exploiting the hidden convexity of the joint range of (non-convex) quadratic functions. We also present numerical examples to illustrate our results.

Keywords: Quadratic Constraint; Joint Range; Quadratic Optimization Problem; Global Optimality Condition; Weak Minimizer (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4419-0437-9_9

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DOI: 10.1007/978-1-4419-0437-9_9

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