The optimization techniques have been employed to a wide range of science, engineering fields and so on. These techniques have attracted a lot of attentions from the researches in both theory and engineering fields. The optimization theory and algorithms have been a hot research issue in both theory and application areas. The intelligent optimization approaches have inspired by nature, which have provided novel ideas and new methods for solving complex problems in engineering fields. It is concluded from no free lunch theorem in optimization field that the hybridization on optimization algorithms is a very effective way to improve the performance of algorithms. Based on the existing intelligent optimization approaches, this book proposes the learnable intelligent optimization approach. It employs the integrated modeling idea which combines the intelligent optimization model with the knowledge model. The intelligent optimization model searches the feasible space of optimization problems according to the mechanism of neighborhood search. The knowledge model discovers some available knowledge from the previous optimization process, and employs the obtained knowledge to guide the subsequent optimization. This book may be interested by the graduated students, scholars in the intelligent optimization, engineering optimization and decision making fields.

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