The max problem revisited
Timo Kötzing, Andrew M. Sutton, Frank Neumann, Una-May O’Reilly · 2012
This paper contributes to the rigorous understanding of genetic programming algorithms by providing runtime complexity analyses of the well-studied Max problem. Several experimental studies have indicated that it is hard to solve the Max problem with crossover-based algorithms. Our analyses show that different variants of the Max problem can provably be solved using simple mutation-based genetic programming algorithms.