Handbook of Formal Optimization
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Beschreibung
The formal optimization handbook is a comprehensive guide that covers a wide range of subjects. It includes a literature review, a mathematical formulation of optimization methods, flowcharts and pseudocodes, illustrations, problems and applications, results and critical discussions, and much more. The book covers a vast array of formal optimization fields, including mathematical and Bayesian optimization, neural networks and deep learning, genetic algorithms and their applications, hybrid optimization methods, combinatorial optimization, constraint handling in optimization methods, and swarm-based optimization. This handbook is an excellent reference for experts and non-specialists alike, as it provides stimulating material. The book also covers research trends, challenges, and prospective topics, making it a valuable resource for those looking to expand their knowledge in this field.
The formal optimization handbook is a comprehensive guide that covers a wide range of subjects. It includes a literature review, a mathematical formulation of optimization methods, flowcharts and pseudocodes, illustrations, problems and applications, results and critical discussions, and much more. The book covers a vast array of formal optimization fields, including mathematical and Bayesian optimization, neural networks and deep learning, genetic algorithms and their applications, hybrid optimization methods, combinatorial optimization, constraint handling in optimization methods, and swarm-based optimization. This handbook is an excellent reference for experts and non-specialists alike, as it provides stimulating material. The book also covers research trends, challenges, and prospective topics, making it a valuable resource for those looking to expand their knowledge in this field.
Rich contributions from leading experts worldwide A complete state-of-the-art reference of the formal optimization methods and applications Includes critical literature review, optimization method description & mathematical formulation, flowcharts, etc
Autor*in
Anand J. Kulkarni
Themen in »Handbook of Formal Optimization«
Engineering Optimization Nature inspired Methods Heuristics Resource Optimization Machine Learning Neural Networks and Deep Learning Optimization in Manufacturing Processes Swarm-based Optimization Physics-based Optimization Bio-inspired Optimization Evolutionary Optimization-based Methods Bayesian Optimization Mathematical Optimization/Programming Constraint Handling in Optimization Methods