computational optimization techniques algorithms de kumar tipu (5 resultados)

Condición: New. In.

Taschenbuch. Condición: Neu. Computational Optimization Techniques: Algorithms and Applications | Rupesh Kumar Tipu (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207806775 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 76 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Computational Optimization Techniques: Algorithms and Applications' provides a comprehensive exploration of optimization methods, ranging from classical techniques like linear and nonlinear programming to advanced metaheuristic algorithms such as genetic algorithms, particle swarm optimization, and ant colony optimization. The book delves into the mathematical foundations of optimization, practical implementations with detailed code examples, and various real-world applications, including engineering design, machine learning, and scheduling problems. Additionally, it highlights the benefits of hybrid metaheuristic methods, combining different algorithms to enhance performance and robustness. This book serves as a valuable resource for students, researchers, and practitioners seeking to understand and apply optimization techniques in diverse fields.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Computational Optimization Techniques: Algorithms and Applications' provides a comprehensive exploration of optimization methods, ranging from classical techniques like linear and nonlinear programming to advanced metaheuristic algorithms such as genetic algorithms, particle swarm optimization, and ant colony optimization. The book delves into the mathematical foundations of optimization, practical implementations with detailed code examples, and various real-world applications, including engineering design, machine learning, and scheduling problems. Additionally, it highlights the benefits of hybrid metaheuristic methods, combining different algorithms to enhance performance and robustness. This book serves as a valuable resource for students, researchers, and practitioners seeking to understand and apply optimization techniques in diverse fields.