Research progress of hardness theories on evolutionary algorithm

The research work of hardness on evolutionary algorithm is an important branch of evolutionary computation. It aims to study the relationship between the performance of evolutionary algorithm and the characters of the optimization problem. And, the goal of the hardness research is estimating the performance of an evolutionary algorithm deployed in one optimization problem by using limited information. This paper summarizes six kinds of hardness theories on evolutionary algorithm, such as fitness-distance correlation model, fitness landscape methods, landscape state machine, optimal contraction theorem, epistasis methods, etc. and eight hardness indicators with them. Furthermore, this paper discusses the advantages and disadvantages of these methods, and prospects the trends of this research field.