Differential Evolution From Theory To Practice


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Differential Evolution: From Theory to Practice


Differential Evolution: From Theory to Practice

Author: B. Vinoth Kumar

language: en

Publisher: Springer Nature

Release Date: 2022-01-25


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This book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable, non-linear and multi-modal objective functions. Many advances have been made recently in differential evolution, from theory to applications. This book comprises contributions which include theoretical developments in DE, performance comparisons of DE, hybrid DE approaches, parallel and distributed DE for multi-objective optimization, software implementations, and real-world applications. The book is useful for researchers, practitioners, and students in disciplines such as optimization, heuristics, operations research and natural computing.

Multi-Objective Optimization in Computational Intelligence: Theory and Practice


Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Author: Thu Bui, Lam

language: en

Publisher: IGI Global

Release Date: 2008-05-31


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Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

Advances in Data-Driven Computing and Intelligent Systems


Advances in Data-Driven Computing and Intelligent Systems

Author: Swagatam Das

language: en

Publisher: Springer Nature

Release Date: 2024-04-10


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The volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2023) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 21 – 23 September 2023. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.