Pseudolinear Functions and Optimization

This is the first book to focus exclusively on pseudolinear functions, a class of generalized convex functions. The book discusses the properties, characterizations, and applications of pseudolinear functions in nonlinear optimization problems. It encompasses nearly all the published literature on the subject along with new results on semi-infinite nonlinear programming problems. The authors present optimality conditions and duality results for many types of optimization problems. They also extend pseudolinear functions to higher-level problems and explore applications to hospital management and economics. Inhaltsverzeichnis Introduction. Pseudolinear Functions: Characterizations and Properties. Constrained Pseudolinear Optimization Problems: Characterizations of Solution Sets. Constrained Pseudolinear Optimization Problems: Characterizations of Solutions Sets in Terms of Lagrange Multipliers. Pseudolinear Multiobjective Optimization. Nonsmooth Pseudolinear Multiobjective Optimization. Static Minimax Programming and Pseudolinear Functions. Nonsmooth Static Minimax Programming and Pseudolinear Functions. Nonsmooth Multiobjective Pseudolinear Programming: Optimality and Duality in Terms of Bifunctions. Pseudolinear Multiobjective Semi-Infinite Programming Problems. Vector Variational Inequality and Vector Pseudolinear Optimization Problems. Extension of Pseudolinear Functions and Variational Inequality Problems. Pseudolinear Functions: Characterizations and Properties of Solution Set. Smooth Pseudolinear Functions and Riemannian Manifolds. Pseudolinear Quadratic Fractional Functions. Pseudolinear Fuzzy Mapping. Pseudolinear Function and Its Applications.