Memetic algorithm for real-time combinatorial stochastic simulation optimization problems with performance analysis.

A three-phase memetic algorithm (MA) is proposed to find a suboptimal solution for real-time combinatorial stochastic simulation optimization (CSSO) problems with large discrete solution space. In phase 1, a genetic algorithm assisted by an offline global surrogate model is applied to find N good diversified solutions. In phase 2, a probabilistic local search method integrated with an online surrogate model is used to search for the approximate corresponding local optimum of each of the N solutions resulted from phase 1.