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Handbook of Optimization: From Classical to Modern Approach

Handbook of Optimization: From Classical to Modern Approach
Kataloginformation
Feldname Details
Vorliegende Sprache eng
Hinweise auf parallele Ausgaben 371944198 Buchausg. u.d.T.: ‡Handbook of optimization
ISBN 978-3-642-30503-0
Name Zelinka, Ivan
Snášel, Václav
ANZEIGE DER KETTE Snášel, Václav
Name Abraham, Ajith
T I T E L Handbook of Optimization
Zusatz zum Titel From Classical to Modern Approach
Verlagsort Berlin ; Heidelberg
Verlag Springer
Erscheinungsjahr 2013
2013
Umfang Online-Ressource (XII, 1100 p. 460 illus, digital)
Reihe Intelligent Systems Reference Library ; 38
Notiz / Fußnoten Description based upon print version of record
Weiterer Inhalt Title; Preface; Contents; ClassicalMethods - Theory; ClassicalMethods - Applications; Heuristics - Theory; Heuristics - Applications; Dynamic Optimization Using Analytic and Evolutionary Approaches: A ComparativeReview; Introduction; Optimal Control and Dynamic Fitness Landscapes; Optimal Control; The Linear Quadratic Control Problem and Its Dynamic Fitness Landscape; Solutions for the General Optimal Control Problem; Evolutionary Computation and Dynamic Fitness Landscapes; Evolutionary Approaches to Dynamic Optimization; Detecting and Reacting to Change; Conclusions; References. Bounded Dual Simplex Algorithm: Definition and StructureBounded Dual Simplex Algorithm; Definitions and Concepts; Chapter Organization; Structure of the Bounded Dual Simplex Algorithm; Bounded Dual Simplex Method; Bounded Dual Simplex in Tableau Format; Algorithm; Bounded Dual Simplex Algorithm with Re-optimization; Application of the Bounded Dual Simplex Algorithm in Electrical Engineering; Transmission Network Expansion Planning Problem; Illustrative Example; Conclusions; References; Some Results on Subanalytic Variational Inclusions; Introduction; Preliminary Results; Divided Differences. Semianalytic and Subanalytic Sets and FunctionsPseudo-Lipschitz Maps; ANewton-TypeMethod; Description of the Method and Assumptions; Convergence Results; The Study of Perturbed Problems; An Iterative Method in the Lipschitz Case; A Secant-Type Method; Conclusion; References; Graph and Geometric Algorithms and Efficient Data Structures; Introduction; Basic Notions; Minimum Spanning Tree Problem; Minimum Network Steiner Tree Problem; Distance Network Approximation (DNA); Euclidean Minimum Spanning Tree Problem; Euclidean Steiner Tree Problem; Robot Motion Planning; Cell Decomposition. Roadmap MethodsConclusions; References; An Exact Algorithm for the Continuous Quadratic Knapsack Problem via Infimal Convolution; Introduction; Theoretical Part; Previous results; Algorithm; The Continuous Quadratic Knapsack Problem; Computational Complexity; Application Part; Economic Dispatch Problem; Large-Scale QP; Computer Code; Conclusions; References; Game Theoretic and Bio-inspired Optimization Approach for Autonomous Movement of MANET Nodes; Introduction; Related Work; Brief Literature Review; Our Previous Work; Background to GT and GA; Game Theory; Genetic Algorithms. Our Node Spreading Bio-inspired GameFinding Next Preferred Locations Using FGA; Our Spatial Game; BioGame Implementation; Simulation Experiments; The Network Area Coverage; The Average Distance Traveled; Simulation of Hostile Attack and Random Node Malfunction; Conclusion; References; Multilocal Programming and Applications; Introduction; Bound Constrained Multilocal Programming; Stochastic Methods; Deterministic Methods; Numerical Experiments; Constrained Multilocal Programming; The Penalty Function Method; Numerical Experiments; Engineering Applications; Phase Stability. Numerical Experiments
Titelhinweis Buchausg. u.d.T.: ‡Handbook of optimization
ISBN ISBN 978-3-642-30504-7
Klassifikation UYQ
COM004000
*90-00
90-06
90C90
006.3
Q342
SK 870
Kurzbeschreibung Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks
2. Kurzbeschreibung Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.
1. Schlagwortkette Optimierung
ANZEIGE DER KETTE Optimierung
SWB-Titel-Idn 373500998
Signatur Springer E-Book
Bemerkungen Elektronischer Volltext - Campuslizenz
Elektronische Adresse $uhttp://dx.doi.org/10.1007/978-3-642-30504-7
Internetseite / Link Volltext
Siehe auch Inhaltsverzeichnis
Siehe auch Inhaltstext
Siehe auch Volltext
Siehe auch Cover
Siehe auch Inhaltstext
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