Abstract
This paper is concerned with duality results for multi objective (m.o.) optimization problems. The core of the paper is a duality theorem derived by usual separation techniques. This theorem generalizes known results in view of the applications to m.o. problems, which are presented in Section 3.
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References
Luenberger, D.G. (1969). Optimization by Vector Space Methods. Wiley, New York.
Pascoletti, A. and Serafini, P. (1984). Scalarizing Vector Optimization Problems. Journal of Optimization Theory and Applications, 42 (4).
Shapiro, J.F. (1979). Mathematical Programming, Structures and Algorithms. Wiley, New York.
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© 1984 Springer-Verlag Berlin Heidelberg
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Serafini, P. (1984). Dual Relaxation and Branch-and-Bound Techniques for Multiobjective Optimization. In: Grauer, M., Wierzbicki, A.P. (eds) Interactive Decision Analysis. Lecture Notes in Economics and Mathematical Systems, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-00184-4_9
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DOI: https://doi.org/10.1007/978-3-662-00184-4_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-13354-4
Online ISBN: 978-3-662-00184-4
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