查询
最新公告

优化算法:针对设计、规划和控制问题的AI技术 By Alaa Khamis

English | 2024 | ISBN: 163343883X | 669 pages | True EPUB | 47.91 MB

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.



Download from free file storage


本站不对文件进行储存,仅提供文件链接,请自行下载,本站不对文件内容负责,请自行判断文件是否安全,如发现文件有侵权行为,请联系管理员删除。