Generalized Convexity and Generalized Monotonicity: Lecture Notes in Economics and Mathematical Systems, cartea 502

Invited Papers.- Minimization of the Sum of Several Linear Fractional Functions.- Discrete Higher Order Convex Functions and their Applications.- Cuts and Semidefinite Relaxations for Nonconvex Quadratic Problems.- Contributed Papers.- The Steiner Ratio of L3p.- Normal Cones to Sublevel Sets: An Axiomatic Approach. Applications in Quasiconvexity and Pseudoconvexity.- Multiobjective Programming with ?-convex Functions.- Rufián-Lizana, Pascual Ruiz-Canales Vector Invex N-set Functions and Minmax Programming.- On the Supremum in Quadratic Fractional Programming.- First and Second Order Characterizations of a Class of Pseudoconcave Vector Functions.- New Invexity-Type Conditions in Constrained Optimization.- Stochastic s-(increasing) Convexity.- Fixed Point Theorems, Coincidence Theorems and Variational Inequalities.- Representation of a Polynomial Function as a Difference of Convex Polynomials, with an Application.- Proper Efficiency and Generalized Convexity in Nonsmooth Vector Optimization Problems.- Duality for Fractional Min-max Problems Involving Arcwise Connected and Generalized Arcwise Connected Functions.- Generalized Convexity for Unbounded Sets: The Enlarged Space.- A Note on Minty Variational Inequalities and Generalized Monotonicity.- On Vector Equilibrium and Vector Variational Inequality Problems.- Stochastic Orders Generated by Generalized Convex Functions.- Separation Theorems for Convex Sets and Convex Functions with Invariance Properties.- Convexity and Generalized Convexity Methods for the Study of Hamilton-Jacobi Equations.- Higher-order Monotone Functions and Probability Theory.- Convexity and Decomposability in Multivalued Analysis.- Scalar Characterization of Generalized Quasiconvex Functions.- Optimality and Wolfe Duality for MultiobjectiveProgramming Problems Involving?-set Functions.- Vector Stochastic Optimization Problems.- On Suprema of Abstract Convex and Quasi-convex Hulls.- Specific Numerical Methods for Solving Some Special Max-min Programming Problems Involving Generalized Convex Functions.