Parameter Control: Strategy or Luck?

Parameter control mechanisms in evolutionary algorithms (EAs) dynamically change the values of the EA parameters during a run. Research over the last two decades has delivered ample examples where an EA using a parameter control mechanism outperforms its static version with fixed parameter values. However, very few have investigated why such parameter control approaches perform bet-ter. In principle, it could be the case that using different parameter values alone is already sufficient and EA performance can be im-proved without sophisticated control strategies. This paper inves-tigates whether very simple random variation in parameter values during an evolutionary run can already provide improvements over static values