Taylor & Francis Ltd Sivumäärä: 230 sivua Asu: Kovakantinen kirja Julkaisuvuosi: 2022, 23.12.2022 (lisätietoa) Kieli: Englanti
The text comprehensively focuses on the concepts, implementation, and application of evolutionary algorithms for predicting, modeling, and optimizing the various material removal processes from their origin to the current advancements. This one-of-a-kind book encapsulates all the features related to the application and implementation of evolutionary algorithms for the purpose of predicting and optimizing the process characteristics of different machining methods and their allied processes that will provide comprehensive information. It broadly explains the concepts of employing evolutionary algorithm-based optimization in a broad domain of various material removal processes. Therefore, this book will enable prospective readers to take full advantage of recent findings and advancements in the fields of traditional, advanced, micro, and hybrid machining, among others. Moreover, the simplicity of its writing will keep readers engaged throughout and make it easier for them to understand the advanced topics.
The book- • Offers a step-by-step guide to implement evolutionary algorithms for the overall optimization of conventional and contemporary machining processes • Provides in-depth analysis of various material removal processes through evolutionary optimization • Details an overview of different evolutionary optimization techniques • Explores advanced processing of various engineering materials-based case studies
It further discusses different nature-inspired algorithms-based modeling, prediction, and modeling of machining responses in attempting advanced machining of the latest materials and related engineering problems along with case studies and practical examples. It will be an ideal reference text for graduate students and academic researchers working in the fields of mechanical engineering, aerospace engineering, industrial engineering, manufacturing engineering, and materials science.
