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.
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Acknowledgements
The authors are grateful to the referees and the guest editor for their helpful comments and valuable suggestions contributed to the final preparation of the chapter. The second author was supported by the Korea Science and Engineering Foundation (KOSEF) NRL Program grant funded by the Korean government (MEST) (No.ROA-2008-000-20010-0).
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Jeyakumar, V., Lee, G.M., Li, G. (2010). Global Optimality Conditions for Classes of Non-convex Multi-objective Quadratic Optimization Problems. In: Burachik, R., Yao, JC. (eds) Variational Analysis and Generalized Differentiation in Optimization and Control. Springer Optimization and Its Applications, vol 47. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0437-9_9
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DOI: https://doi.org/10.1007/978-1-4419-0437-9_9
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