A new algorithm for stochastic discrete resource allocation optimization

Stochastic discrete resource allocation problems are difficult to solve. In this paper, we propose a new algorithm designed specifically to tackle the m. The algorithm combines with the Nested Partitions method, the Ordinal Op timization techniques, and an efficient simulation control technique. The r esulting hybrid algorithm retains the global perspective of the Nested Part itions method and the fast convergence properties of the Ordinal Optimizati on. Numerical results demonstrate that the hybrid algorithm can be effectiv ely used for many large-scale stochastic discrete optimization problems.