Stochastic discrete resource allocation optimization

Stochastic discrete resource allocation problems are difficult to solve. In this paper, we propose a new algorithm for solving such difficult problems. The algorithm combines with the nested partitions method, the ordinal optimization techniques, and an efficient ranking and selection method. The resulting hybrid algorithm retains the global perspective of the nested partitions method and the fast convergence properties of the ordinal optimization. Numerical results demonstrate that the hybrid algorithm can be effectively applied to a large-scale discrete resource allocation problems