Advances in Metaheuristics Algorithms: Methods and Applications

Advances in Metaheuristics Algorithms: Methods and Applications

Erik Cuevas , Daniel Zaldivar , Marco Perez-Cisneros
아직 평점이 없습니다
2018 · 영어 · 페이퍼백 · 판본 2개
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설명

In a rapidly evolving field, this work provides a comprehensive exploration of innovative metaheuristic algorithms that have gained traction in solving complex optimization problems. The authors, experts in their respective domains, present groundbreaking methodologies that push the boundaries of traditional computational approaches. With a blend of theoretical insights and practical applications, they illuminate the diverse ways these algorithms can be tailored to meet various challenges across multiple disciplines.

Readers will find detailed discussions on the evolution of these algorithms, highlighting both their strengths and limitations. The authors meticulously document their findings, emphasizing empirical analyses that validate the effectiveness of these newly developed techniques. Each chapter is thoughtfully structured, allowing readers to grasp intricate concepts while being guided through real-world examples that demonstrate the applicability of metaheuristics.

Overall, this work serves as a vital resource for researchers, practitioners, and students eager to delve into the future of optimization methods. Its forward-thinking perspective encourages a deeper understanding of metaheuristics, inspiring further exploration and development in this dynamic area of research.

책 세부 정보

형식 페이퍼백
페이지 232 페이지
언어 영어
출판됨 12월 14, 2018
출판사 Springer
ISBN-10 3030077365
ISBN-13 9783030077365
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