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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:
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.
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.
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
Elegantly covers modern optimization algorithms in depth and breadth. A great resource.
A treasure trove. Perfect for anyone looking to navigate the intricate world of optimization in real-world scenarios.
An exceptional book on the most prominent optimization algorithms.
This little gem introduces the reader to the algorithms and how you should apply them to real-world problems. A must-read!
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