DE-TDQL: An adaptive memetic algorithm

Memetic algorithms are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolution. In this paper a synergism of the classical Differential Evolution algorithm and Q-learning is used to construct the memetic algorithm. Computer simulation with standard benchmark functions reveals that the proposed memetic algorithm outperforms three distinct Differential Evolution algorithms.