A01=Victor Parada
advanced optimisation algorithm design
Age Group_Uncategorized
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algorithm selection strategies
Author_Victor Parada
automatic-update
Category1=Non-Fiction
Category=PBD
Category=PBT
Category=PBU
Category=PBV
Category=TJFM
Category=UB
Category=UMB
Category=UMX
Category=UMZ
Category=UYQ
Category=UYQM
combinatorial optimisation
COP=United Kingdom
Delivery_Pre-order
eq_bestseller
eq_computing
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
evolutionary computation
Language_English
NP-hard problems
PA=Not yet available
Price_€100 and above
PS=Forthcoming
reinforcement learning methods
softlaunch
symbolic regression techniques
Product details
- ISBN 9781032894454
- Weight: 553g
- Dimensions: 156 x 234mm
- Publication Date: 10 Feb 2025
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
- Language: English
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In the rapidly evolving domain of computational problem-solving, this book delves into the cutting-edge Automatic Generation of Algorithms (AGA) paradigm, a groundbreaking approach poised to redefine algorithm design for optimization problems. Spanning combinatorial optimization, machine learning, genetic programming, and beyond, it investigates AGA's transformative capabilities across diverse application areas. The book initiates by introducing fundamental combinatorial optimization concepts and NPhardness significance, laying the foundation for understanding AGA's necessity and potential. It then scrutinizes the pivotal Master Problem concept in AGA and the art of modeling for algorithm generation. The exploration progresses with integrating genetic programming and synergizing AGA with evolutionary computing. Subsequent chapters delve into the AGA-machine learning intersection, highlighting their shared optimization foundation while contrasting divergent objectives. The automatic generation of metaheuristics is examined, aiming to develop versatile algorithmic frameworks adaptable to various optimization problems. Furthermore, the book explores applying reinforcement learning techniques to automatic algorithm generation. Throughout, it invites readers to reimagine algorithmic design boundaries, offering insights into AGA's conceptual underpinnings, practical applications, and future directions, serving as an invitation for researchers, practitioners, and enthusiasts in computer science, operations research, artificial intelligence, and beyond to embark on a journey toward computational excellence where algorithms are born, evolved, and adapted to meet ever-changing real-world problem landscapes.
Victor Parada is Titular Professor in the Informatics Engineering Department at the University of Santiago, Chile.
