Fixed Point Theory, Variational Analysis, and Optimization

Fixed Point Theory, Variational Analysis, and Optimization
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DOI:
10.1201/b17068
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发表时间:
2014-06
期刊:
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影响因子:
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通讯作者:
S. Al-Mezel;F. Al-Solamy;Q. Ansari
S. Al-Mezel;F. Al-Solamy;Q. Ansari
中科院分区:
其他
文献类型:
--
作者:
S. Al-Mezel;F. Al-Solamy;Q. Ansari

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Preface List of Figures List of Tables Contributors I. Fixed Point Theory Common Fixed Points in Convex Metric Spaces Abdul Rahim Khan and Hafiz Fukhar-ud-din Introduction Preliminaries Ishikawa Iterative Scheme Multistep Iterative Scheme One-Step Implicit Iterative Scheme Bibliography Fixed Points of Nonlinear Semigroups in Modular Function Spaces B. A. Bin Dehaish and M. A. Khamsi Introduction Basic Definitions and Properties Some Geometric Properties of Modular Function Spaces Some Fixed-Point Theorems in Modular Spaces Semigroups in Modular Function Spaces Fixed Points of Semigroup of Mappings Bibliography Approximation and Selection Methods for Set-Valued Maps and Fixed Point Theory Hichem Ben-El-Mechaiekh Introduction Approximative Neighborhood Retracts, Extensors, and Space Approximation Approximative Neighborhood Retracts and Extensors Contractibility and Connectedness Contractible Spaces Proximal Connectedness Convexity Structures Space Approximation The Property A(K P) for Spaces Domination of Domain Domination, Extension, and Approximation Set-Valued Maps, Continuous Selections, and Approximations Semicontinuity Concepts USC Approachable Maps and Their Properties Conservation of Approachability Homotopy Approximation, Domination of Domain, and Approachability Examples of A-Maps Continuous Selections for LSC Maps Michael Selections A Hybrid Continuous Approximation-Selection Property More on Continuous Selections for Non-Convex Maps Non-Expansive Selections Fixed Point and Coincidence Theorems Generalizations of the Himmelberg Theorem to the Non-Convex Setting Preservation of the FPP from P to A(K P) A Leray-Schauder Alternative for Approachable Maps Coincidence Theorems Bibliography II. Convex Analysis and Variational Analysis Convexity, Generalized Convexity, and Applications N. Hadjisavvas Introduction Preliminaries Convex Functions Quasiconvex Functions Pseudoconvex Functions On the Minima of Generalized Convex Functions Applications Sufficiency of the KKT Conditions Applications in Economics Further Reading Bibliography New Developments in Quasiconvex Optimization D. Aussel Introduction Notations The Class of Quasiconvex Functions Continuity Properties of Quasiconvex Functions Differentiability Properties of Quasiconvex Functions Associated Monotonicities Normal Operator: A Natural Tool for Quasiconvex Functions The Semistrictly Quasiconvex Case The Adjusted Sublevel Set and Adjusted Normal Operator Adjusted Normal Operator: Definitions Some Properties of the Adjusted Normal Operator Optimality Conditions for Quasiconvex Programming Stampacchia Variational Inequalities Existence Results: The Finite Dimensions Case Existence Results: The Infinite Dimensional Case Existence Result for Quasiconvex Programming Bibliography An Introduction to Variational-Like Inequalities Qamrul Hasan Ansari Introduction Formulations of Variational-Like Inequalities Variational-Like Inequalities and Optimization Problems Invexity Relations between Variational-Like Inequalities and an Optimization Problem Existence Theory Solution Methods Auxiliary Principle Method Proximal Method Appendix Bibliography III. Vector Optimization Vector Optimization: Basic Concepts and Solution Methods Dinh The Luc and Augusta Ratiu Introduction Mathematical Backgrounds Partial Orders Increasing Sequences Monotone Functions Biggest Weakly Monotone Functions Pareto Maximality Maximality with Respect to Extended Orders Maximality of Sections Proper Maximality and Weak Maximality Maximal Points of Free Disposal Hulls Existence The Main Theorems Generalization to Order-Complete Sets Existence via Monotone Functions Vector Optimization Problems Scalarization Optimality Conditions Differentiable Problems Lipschitz Continuous Problems Concave Problems Solution Methods Weighting Method Constraint Method Outer Approximation Method Bibliography Multi-Objective Combinatorial Optimization Matthias Ehrgott and Xavier Gandibleux Introduction Definitions and Properties Two Easy Problems: Multi-Objective Shortest Path and Spanning Tree Nice Problems: The Two-Phase Method The Two-Phase Method for Two Objectives The Two-Phase Method for Three Objectives Difficult Problems: Scalarization and Branch and Bound Scalarization Multi-Objective Branch and Bound Challenging Problems: Metaheuristics Conclusion Bibliography Index