Titlebook: Data-Driven Evolutionary Optimization; Integrating Evolutio Yaochu Jin,Handing Wang,Chaoli Sun Book 2021 The Editor(s) (if applicable) and

清真寺

Yaochu Jin,Handing Wang,Chaoli SunIncludes a brief introduction to mathematical programming, metaheuristic algorithms, and machine learning techniques.Presents a systematic description of most recent research advances in data-driven e

antenna

Abduct

G. I. Marchouk,V. V. ShaydourovThis chapter briefly introduces the most widely used traditional optimization algorithms, including the gradient based method and its variants, basic methods for constrained optimization, pattern search for non-differentiable or black-box optimization problems, and deterministic global optimization methods.

伙伴

Classical Optimization Algorithms,This chapter briefly introduces the most widely used traditional optimization algorithms, including the gradient based method and its variants, basic methods for constrained optimization, pattern search for non-differentiable or black-box optimization problems, and deterministic global optimization methods.

思想灵活

斜

Evolutionary and Swarm Optimization,gies, genetic programming, ant colony optimization algorithms, particle swarm optimization, and differential evolution. In addition, memetic algorithms that combine evolutionary search with local search, and estimation of distribution algorithms that use a probabilistic model to generate offspring s