Introduction to mathematical optimization
Book information
Description
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.
Similar books
Proceedings of Eighth International Congress on Information and Communication Technology: ICICT 2023, London, Volume 4
2023 · EPUB
Proceedings of Eighth International Congress on Information and Communication Technology: ICICT 2023, London, Volume 4
2023 · PDF
Evolution in Computational Intelligence: Proceedings of the 10th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2022)
2023 · PDF
Intelligent Data Engineering and Analytics: Proceedings of the 10th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2022)
2023 · PDF
Proceedings of Seventh International Congress on Information and Communication Technology: ICICT 2022, London, Volume 3
2022 · PDF
Proceedings of Sixth International Congress on Information and Communication Technology: ICICT 2021, London, Volume 2
2021 · PDF
Proceedings of Fifth International Congress on Information and Communication Technology: ICICT 2020, London, Volume 2
2021 · PDF
Proceedings of Fifth International Congress on Information and Communication Technology: ICICT 2020, London, Volume 1
2021 · PDF