Abstract
This article summarizes the basic ideas of convex optimization in finite-dimensional vector spaces. Duality, the Fenchel transforms and the subdifferential are introduced and used to discuss Lagrangean duality and the Kuhn–Tucker theorem. Applications of these ideas can be found in duality.
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Bibliography
Arrow, K., L. Hurwicz, and H. Uzawa. 1961. Constraint qualifications in maximization problems. Naval Logistics Research Quarterly 8: 175–191.
Mas-Colell, A., and W. Zame. 1991. Equilibrium theory in infinite dimensional spaces. In Handbook of mathematical economics, ed. W. Hildenbrand and H. Sonnenschein, vol. 4. Amsterdam: North-Holland.
Rockafellar, R.T. 1970. Convex analysis. Princeton: Princeton University Press.
Rockafellar, R.T. 1974. Conjugate duality and opttimization, CBMS Regional Conference Series No. 16. Philadelphia: SIAM.
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Blume, L.E. (2018). Convex Programming. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_591
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DOI: https://doi.org/10.1057/978-1-349-95189-5_591
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Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-95188-8
Online ISBN: 978-1-349-95189-5
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