Optimization Algorithms : AI Techniques for Design, Planning, and Control Problems

Alaa Khamis

ISBN 10: 163343883X / ISBN 13: 9781633438835

Editore: Manning Publications Sep 2024, 2024

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Neuware - Solve design, planning, and control problems using modern AI techniques.Optimization problems are everywhere in daily life. What s the fastest route from one place to another How do you calculate the optimal price for a product How should you plant crops, allocate resources, and schedule surgeries Optimization Algorithms introduces the AI algorithms that can solve these complex and poorly-structured problems. In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn: The core concepts of search and optimization Deterministic and stochastic optimization techniques Graph search algorithms Trajectory-based optimization algorithms Evolutionary computing algorithms Swarm intelligence algorithms Machine learning methods for search and optimization problems Efficient trade-offs between search space exploration and exploitation State-of-the-art Python libraries for search and optimization Inside this comprehensive guide, you ll find a wide range of optimization methods, from deterministic search algorithms to stochastic derivative-free metaheuristic algorithms and machine learning methods. Don t worry there s no complex mathematical notation. You ll learn through in-depth case studies that cut through academic complexity to demonstrate how each algorithm works in the real world. Plus, get hands-on experience with practical exercises to optimize and scale the performance of each algorithm. Purchase of the print book includes a free Elektronisches Buch in PDF and ePub formats from Manning Publications. About the technology Every time you call for a rideshare, order food delivery, book a flight, or schedule a hospital appointment, an algorithm works behind the scenes to find the optimal result. Blending modern AI methods with classical search and optimization techniques can deliver incredible results, especially for the messy problems you encounter in the real world. This book shows you how. About the book Optimization Algorithms explains in clear language how optimization algorithms work and what you can do with them. This engaging book goes beyond toy examples, presenting detailed scenarios that use actual industry data and cutting-edge AI techniques. You will learn how to apply modern optimization algorithms to real-world problems like pricing products, matching supply with demand, balancing assembly lines, tuning parameters, coordinating mobile networks, and cracking smart mobility challenges. What's inside Graph search algorithms Metaheuristic algorithms Machine learning methods State-of-the-art Python libraries for optimization Efficient trade-offs between search space exploration and exploitation About the reader Requires intermediate Python and machine learning skills. About the author Dr. Alaa Khamis is an AI and smart mobility technical leader at General Motors and a lecturer at the University of Toronto. The technical editor on this book was Frances Buontempo. Table of Contents PART 1 1 Introduction to search and optimization 2 A deeper look at search and optimization 3 Blind search algorithms 4 Informed search algorithms PART 2 5 Simulated annealing 6 Tabu search PART 3 7 Genetic algorithms 8 Genetic algorithm variants PART 4 9 Particle swarm optimization 10 Other swarm intelligence algorithms to explore PART 5 11 Supervised and unsupervised learning 12 Reinforcement learning included with the Elektronisches Buch only: Appendix A Appendix B Appendix C.

Codice articolo 9781633438835

Dati bibliografici

• Titolo: Optimization Algorithms : AI Techniques for Design, Planning, and Control Problems
• Editore: Manning Publications Sep 2024
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 163343883X
• ISBN 13: 9781633438835
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 232 L x 186 A x 30 P (millimetri) 232 millimetri di larghezza per 186 millimetri di altezza per 30 millimetri di profondità
• Peso: 908 grammi

Descrizione articolo

Riassunto

Solve design, planning, and control problems using modern machine learning and AI techniques.

In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn:
 

• Machine learning methods for search and optimization problems
• The core concepts of search and optimization
• Deterministic and stochastic optimization techniques
• Graph search algorithms
• Nature-inspired search and optimization algorithms
• Efficient trade-offs between search space exploration and exploitation
• State-of-the-art Python libraries for search and optimization

Optimization problems are everywhere in daily life. What’s the fastest route from one place to another? How do you calculate the optimal price for a product? How should you plant crops, allocate resources, and schedule surgeries? Optimization Algorithms introduces the AI algorithms that can solve these complex and poorly-structured problems. Inside you’ll find a wide range of optimization methods, from deterministic and stochastic derivative-free optimization to nature-inspired search algorithms and machine learning methods. Don’t worry—there’s no complex mathematical notation. You’ll learn through in-depth case studies that cut through academic complexity to demonstrate how each algorithm works in the real world.

About the technology

Search and optimization algorithms are powerful tools that can help practitioners find optimal or near-optimal solutions to a wide range of design, planning and control problems. When you open a route planning app, call for a rideshare, or schedule a hospital appointment, an AI algorithm works behind the scenes to make sure you get an optimized result. This guide reveals the classical and modern algorithms behind these services.

About the book

Optimization Algorithms: AI techniques for design, planning, and control problems explores the AI algorithms that determine the most efficient routes, optimal designs, and solve other logistical issues. Dive into the exciting world of classical problems like the Travelling Salesman Problem and the Knapsack Problem, as well as cutting-edge modern implementations like graph search methods, metaheuristics and machine learning. Discover how to use these algorithms in real-world situations, with in-depth case studies on assembly line balancing, fitness planning, rideshare dispatching, routing and more. Plus, get hands-on experience with practical exercises to optimize and scale the performance of each algorithm.

About the reader

For AI practitioners familiar with the Python language.

About the author

Dr. Alaa Khamis is an AI and smart mobility technical leader at General Motors and a sessional lecturer at the University of Toronto. He is also an adjunct professor at Ontario Tech University and Nile University, affiliate member of the Center of Pattern Analysis and Machine Intelligence (CPAMI) at the University of Waterloo, and a former professor of artificial intelligence and robotics.

 

Informazioni sull?autore

Dr. Alaa Khamis is an AI and smart mobility technical leader at General Motors and a sessional lecturer at the University of Toronto. He is also an adjunct professor at Ontario Tech University and Nile University, affiliate member of the Center of Pattern Analysis and Machine Intelligence (CPAMI) at the University of Waterloo, and a former professor of artificial intelligence and robotics.