{"product_id":"optimization-algorithms","title":"Optimization Algorithms","description":"\u003cp\u003e\u003cb\u003eSolve design, planning, and control problems using modern machine learning and AI techniques.\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIn \u003ci\u003eOptimization Algorithms: AI techniques for design, planning, and control problems\u003c\/i\u003e you will learn:\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMachine learning methods for search and optimization problems\u003c\/li\u003e\n\u003cli\u003eThe core concepts of search and optimization\u003c\/li\u003e\n\u003cli\u003eDeterministic and stochastic optimization techniques\u003c\/li\u003e\n\u003cli\u003eGraph search algorithms\u003c\/li\u003e\n\u003cli\u003eNature-inspired search and optimization algorithms\u003c\/li\u003e\n\u003cli\u003eEfficient trade-offs between search space exploration and exploitation\u003c\/li\u003e\n\u003cli\u003eState-of-the-art Python libraries for search and optimization\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eOptimization 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? \u003ci\u003eOptimization Algorithms\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout The Technology\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eSearch 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout The Book\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eOptimization Algorithms: AI techniques for design, planning, and control problems \u003c\/i\u003eexplores 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout The Author\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr. Alaa Khamis\u003c\/b\u003e 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.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eEbook License\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eEnd-User Warranty And License Agreement\u003c\/p\u003e\u003cp\u003e1. Grant Of License\u003c\/p\u003e\u003cp\u003eManning Has Authorized The Download By You Of An Unrestricted Number Of Copies Of The Electronic Book (Ebook) In Any Of The Available Formats. 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