A General Analysis of Evolutionary Algorithms for Hard and Easy Fitness Functions

This paper presents a general analysis of evolutionary algorithms for solving hard and easy fitness functions. Two results are proven in the paper: (1) using lower selection pressure is better for solving hard fitness functions; (2) the strong cut-of point is 1 for solving any easy fitness function, which means it brings no benefit if using a population size larger than 1.