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Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms.
The book investigates the application of intelligent optimization techniques to solve complex computational problems. It explores how computational intelligence mechanisms are employed to refine feature models and design effective optimization algorithms, aiming for optimal or satisfactory solutions. The text highlights advancements in algorithms such as evolutionary algorithms, whale optimization, differential evolution, and particle swarm optimization, detailing their role in addressing challenges like green shop scheduling, nonlinear inversion, and logistics distribution. The editors posit that this collection will foster new discoveries in intelligent algorithms.
This collection is presented as a valuable resource for researchers focused on intelligent algorithms, aiming to open new avenues for improvement and discovery. The editors highlight the book's role in understanding the principles and design of these algorithms. The content covers advancements in various optimization techniques and their application to challenging real-world problems. The book is intended to provide insights into achieving better optimization quality, efficiency, and performance.
Page Count:
442
Publication Date:
2021-12-03
Publisher:
MDPI AG
ISBN-10:
3036523944
ISBN-13:
9783036523941
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