Abstract: Intelligent optimization algorithms have been successfully applied to solveing complex and challenging combinatorial optimization problems. However， these manually designed algorithms relying on multi-domain expertise are often abandoned after solving specific problem instances， resulting in a waste of computing resources. Therefore， automated algorithm design has gradually become a research hotspot in the field of intelligent optimization intelligent algorithms. We provide a systematic review of the automated design method of intelligent optimization algorithms. Firstly， we investigate the relevant literature publication of and keyword clustering to analyze the development trend and acquire three hot research topics by using bibliometrics： Algorithm configuration， algorithm selection， and algorithm composition. Secondly， we review the existing automated algorithm design methods and frameworks， summarizing their advantages and disadvantages and analyzing their applicability in different problem scenarios. Finally， we present future research directions for automated algorithm design.