Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels
Duc-Cuong Dang, Per Kristian Lehre · 2014
Recently, an easy-to-use fitness-level technique was introduced to prove upper bounds on the expected runtime of randomised search heuristics with non-elitist populations and unary variation operators. Following this work, we present a new and much more detailed analysis of the population dynamics, leading to a significantly improved fitness-level technique. In addition to improving the technique, the proof has been simplified.