On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms

The interplay between the mutation operator and the selection mechanism plays a fundamental role in the behaviour of evolutionary algorithms (EAs). However, this interplay is still not completely understood. This paper presents a rigorous runtime analysis of a non-elitistic population based EA that uses the linear ranking selection mechanism. The analysis focuses on how the balance between parameter controlling the selection pressure in linear ranking selection, and parameter controlling the bit-wise mutation rate impact the expected runtime. The results point out situations where a correct balance between selection pressure and mutation rate is essential for finding the optimal solution in polynomial time. In particular, it is shown that there exist fitness functions which can only be solved in polynomial time if the ratio between parameters and is within a narrow critical interval, and where a small change in this ratio can increase the runtime exponentially. Furthermore, it is ...

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Per Kristian Lehre, Xin Yao
• Keywords: CORR 2010, Education, Mutation Rate, Selection, Selection Pressure