Intelligent Optimization Algorithm Theory and Applications
Language: English
Published by MDPI AG, 2026
- Hardcover
- New
Condition: New
£ 141.49
Quantity: 2 available
Add to basketItem description from seller
Intelligent optimization algorithms (IOAs) are a branch of artificial intelligence that emphasizes developing and applying data-driven methods to solve complex search, learning, and simulation problems. Many real-world applications for complex industrial engineering or design problems could be modeled as searching, learning, and simulation problems. Given their learning ability, IOAs are emerging approaches that utilize advanced computational power, metaheuristic algorithms, and massive data processing techniques. These approaches have been actively investigated and applied to many real-world applications, such as scheduling and logistics operations.IOAs, inspired by biological or social phenomena, encompass a range of search and optimization techniques. They include bio-inspired intelligent algorithms, evolutionary computation methods, and swarm intelligence. With these methods, optimization problems, which can be formulated in any form, do not need to be expressed as continuous, differentiable functions. The only requirement for representing optimization problems is to evaluate each individual by its fitness value. Therefore, IOAs are used to solve more general optimization problems, especially those that are difficult to solve with traditional hill-climbing algorithms. Sprache: Englisch Gewicht in Gramm: 973. …
Seller Inventory # IB-488439
- Title
- Intelligent Optimization Algorithm Theory and Applications
- Publisher
- MDPI AG
- Publication year
- 2026
- Condition
- Neu
- Binding
- Gebundene Ausgabe
- Language
- English
- ISBN 10
- 3725888396
- ISBN 13
- 9783725888399
- Item weight
- 973 grams
Intelligent optimization algorithms (IOAs) are a branch of artificial intelligence that emphasizes developing and applying data-driven methods to solve complex search, learning, and simulation problems. Many real-world applications for complex industrial engineering or design problems could be modeled as searching, learning, and simulation problems. Given their learning ability, IOAs are emerging approaches that utilize advanced computational power, metaheuristic algorithms, and massive data processing techniques. These approaches have been actively investigated and applied to many real-world applications, such as scheduling and logistics operations.
IOAs, inspired by biological or social phenomena, encompass a range of search and optimization techniques. They include bio-inspired intelligent algorithms, evolutionary computation methods, and swarm intelligence. With these methods, optimization problems, which can be formulated in any form, do not need to be expressed as continuous, differentiable functions. The only requirement for representing optimization problems is to evaluate each individual by its fitness value. Therefore, IOAs are used to solve more general optimization problems, especially those that are difficult to solve with traditional hill-climbing algorithms.
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