Abstract
A global optimization approach for convex multiplicative problems based on the generalized Benders decomposition is proposed. A suitable representation of the multiplicative problem in the outcome space reduces its global solution to the solution of a sequence of quasiconcave minimizations over polytopes. Some similarities between convex multiplicative and convex multiobjective programming become evident through the methodology proposed. The algorithm is easily implemented; its performance is illustrated by a test problem.
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© 2005 Springer-Verlag Berlin Heidelberg
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Oliveira, R.M., Ferreira, P.A.V. (2005). Global Optimization of Convex Multiplicative Programs by Duality Theory. In: Jermann, C., Neumaier, A., Sam, D. (eds) Global Optimization and Constraint Satisfaction. COCOS 2003. Lecture Notes in Computer Science, vol 3478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425076_8
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DOI: https://doi.org/10.1007/11425076_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26003-5
Online ISBN: 978-3-540-32041-8
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