How hard should we run?
Yun-Geun Lee, Bob McKay · 2011
All evolutionary algorithms trade off exploration and exploitation in optimisation problems; dynamic problems are no exception. We investigate this trade-off, over a range of algorithm settings, on dynamic variants of three well-known optimisation problems (One Max, Royal Road and knapsack), using Yang's XOR method to vary the scale and rate of change. Extremely exploitative algorithm settings performed best for a surprisingly wide range of problems; even where they were not the most effective, they still performed competitively, and even in those cases, the best performers were still far more exploitative than most would anticipate.