Introduction to mathematical optimization : from linear programming to metaheuristics / / Xin-She Yang

• Autore: Yang Xin-She
• Pubblicazione: Cambridge, UK, : Cambridge International Science Publishing, c2008
• Descrizione fisica: 1 online resource (160 p.)
• Soggetto topico: Mathematical optimization; Mathematical analysis
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: ""Contents""; ""Preface""; ""1. Mathematical Optimization""; ""1.1 Optimization""; ""1.2 Optimality Criteria""; ""1.3 Computational Complexity""; ""1.4 NP-Complete Problems""; ""2. Norms and Hessian Matrices""; ""2.1 Vector and Matrix Norms""; ""2.2 Eigenvalues and Eigenvectors""; ""2.3 Spectral Radius of Matrices""; ""2.4 Hessian Matrix""; ""2.5 Convexity""; ""3. Root-Finding Algorithms""; ""3.1 Simple Iterations""; ""3.2 Bisection Method""; ""3.3 Newtonâ€?s Method""; ""3.4 Iteration Methods""; ""4. System of Linear Equations""; ""4.1 Linear systems""; ""4.2 Gauss Elimination"" ; ""4.3 Gauss-Jordan Elimination""""4.4 LU Factorization""; ""4.5 Iteration Methods""; ""4.5.1 Jacobi Iteration Method""; ""4.5.2 Gauss-Seidel Iteration""; ""4.5.3 Relaxation Method""; ""4.6 Nonlinear Equation""; ""4.6.1 Simple Iterations""; ""4.6.2 Newton-Raphson Method""; ""5. Unconstrained Optimization""; ""5.1 Univariate Functions""; ""5.2 Multivariate Functions""; ""5.3 Gradient-Based Methods""; ""5.3.1 Newtonâ€?s Method""; ""5.3.2 Steepest Descent Method""; ""5.4 Hooke-Jeeves Pattern Search""; ""6.Linear Mathematical Programming""; ""6.1 Linear Programming""; ""6.2 Simplex Method"" ; ""6.2.1 Basic Procedure""""6.2.2 Augmented Form""; ""6.2.3 A Case Study""; ""7. Nonlinear Optimization""; ""7.1 Penalty Method""; ""7.2 Lagrange Multipliers""; ""7.3 Kuhn-Tucker Conditions""; ""7.4 No Free Lunch Theorems""; ""8. Tabu Search""; ""8.1 Tabu Search""; ""8.2 Travelling Salesman Problem""; ""8.3 Tabu Search for TSP""; ""9. Ant Colony Optimization""; ""9.1 Behaviour of Ants""; ""9.2 Ant Colony Optimization""; ""9.3 Double Bridge Problem""; ""9.4 Multi-Peak Functions""; ""10. Particle Swarm Optimization""; ""10.1 Swarm Intelligence""; ""10.2 PSO algorithms""; ""10.3 Accelerated PSO"" ; ""10.4 Multimodal Functions""""10.5 Implementation""; ""10.6 Constraints""; ""11. Simulated Annealing""; ""11.1 Fundamental Concepts""; ""11.2 Choice of Parameters""; ""11.3 SA Algorithm""; ""11.4 Implementation""; ""12. Multiobjective Optimization""; ""12.1 Pareto Optimality""; ""12.2 Weighted Sum Method""; ""12.3 Utility Method""; ""12.4 Metaheuristic Search""; ""12.5 Other Algorithms""; ""Bibliography""; ""Index""
• Sommario/riassunto: This book strives to provide a balanced coverage of efficient algorithms commonly used in solving mathematical optimization problems. It covers both the convectional algorithms and modern heuristic and metaheuristic methods. Topics include gradient-based algorithms such as Newton-Raphson method, steepest descent method, Hooke-Jeeves pattern search, Lagrange multipliers, linear programming, particle swarm optimization (PSO), simulated annealing (SA), and Tabu search. Multiobjective optimization including important concepts such as Pareto optimality and utility method is also described. Three Matlab and Octave programs so as to demonstrate how PSO and SA work are provided. An example of demonstrating how to modify these programs to solve multiobjective optimization problems using recursive method is discussed.
• Titolo autorizzato: Introduction to mathematical optimization
• ISBN: 1-907343-66-0; 1-904602-91-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910962802103321
• Lo trovi qui: Univ. Federico II