Introduction to mathematical optimization: from linear programming to metaheuristics
Material type:
TextPublication details: New Delhi: Cambridge International Science Pub., 2009. Description: (vi, 150 pages) : illustrations; 23 cmISBN: 81-309-1114-0 (hbk.)Subject(s): MATHEMATICS | Game TheoryDDC classification: 519.3 YAN Summary: Annotation. 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
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Book
|
Teaching & Research Resource Centre - 1 - Economics, Mathematics and Statistics | 519.3 YAN (Browse shelf(Opens below)) | 1 | Available | M-40031 |
Includes bibliographical references and Index
Annotation. 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
There are no comments on this title.