Runtime Analysis of a Compact Genetic Algorithm with High Selection Pressure

The Compact Genetic Algorithm (cGA) is an estimation-of-distribution algorithm that has been receiving much attention especially in the runtime analysis community in recent years. It comes with a single parameter K determining its strength of updates. Contrary to other estimation-of-distribution algorithms like the UMDA, the standard cGA does not have a parameter controlling its selection pressure.