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Data-Driven Evolutionary Optimization

Integrating Evolutionary Computation, Machine Learning and Data Science

Yaochu Jin; Handing Wang; Chaoli Sun

978-3-030-74640-7

2021
Edition 1
- Includes a brief introduction to mathematical programming, metaheuristic algorithms, and machine learning techniques
- Presents a systematic description of most recent research advances in data-driven evolutionary optimization, including surrogate-assisted single-, multi-, and many-objective optimization
- Introduces various intuitive and mathematical surrogate management strategies, such as the trust region method and acquisition functions in Bayesian optimization
- Provides applications of data-driven optimization to engineering design, automation of process industry, health care, and automated machine learning
€340

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