Generalized Convexity, Generalized Monotonicity and Applications: Proceedings of the 7th International Symposium on Generalized Convexity and Generalized Monotonicity
Andrew Eberhard, Nicolas Hadjisavvas, D.T. Luc
Springer Science & Business Media, Jun 22, 2006 - Business & Economics - 350 pages
In recent years there is a growing interest in generalized convex fu- tions and generalized monotone mappings among the researchers of - plied mathematics and other sciences. This is due to the fact that mathematical models with these functions are more suitable to describe problems of the real world than models using conventional convex and monotone functions. Generalized convexity and monotonicity are now considered as an independent branch of applied mathematics with a wide range of applications in mechanics, economics, engineering, finance and many others. The present volume contains 20 full length papers which reflect c- rent theoretical studies of generalized convexity and monotonicity, and numerous applications in optimization, variational inequalities, equil- rium problems etc. All these papers were refereed and carefully selected from invited talks and contributed talks that were presented at the 7th International Symposium on Generalized Convexity/Monotonicity held in Hanoi, Vietnam, August 27-31, 2002. This series of Symposia is or- nized by the Working Group on Generalized Convexity (WGGC) every 3 years and aims to promote and disseminate research on the field. The WGGC (http://www.genconv.org) consists of more than 300 researchers coming from 36 countries.
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algorithm analysis Asplund assume Banach Banach spaces Borwein bounded Cambini closed convex co-coercive coderivatives compact computing concave consider constraint systems convergence convex analysis convex cone convex functions convex program convex set defined Definition denote derivatives differentiable downward sets dual problem duality entropy equivalent Ermoliev exists feasible solution finite fractional programming global optimization Hence hidden convex Hilbert space holds integral invex iteration Journal of Optimization Lemma linear fractional Lipschitz continuous lower semicontinuous Mathematical Programming matrix mollifiers Mordukhovich multifunctions multivalued map nonconvex nonempty nonexpansive Nonlinear nonsmooth Noor normal objective function obtain optimal solution optimality conditions optimization problems Optimization Theory polyblock polynomial programming problem Proof Proposition pseudoconvex pseudolinear quadratic regular Rockafellar satisfies scalar Schaible semicontinuous sequence set constraint SIAM solving space strongly monotone subdifferential subgradient subset Theorem 3.1 Theory and Applications tions upper extreme point variational inequality variational inequality problem vector optimization vertex