Managing stochastic, finite capacity, multi-project systems through the cross-entropy methodology

This paper addresses the problem of loading a finite capacity, stochastic (random) and dynamic multi-project system. The system is controlled by keeping a constant number of projects concurrently in the system. A new approach, based on the Cross-Entropy (CE) method, is proposed to determine optimal loading of the system. Through numerical experiments, we demonstrate the CE method performance and show new insights into its behavior in a noisy system. Particularly, we suggest a trade-off between the convergence time, the number of iterations and the noise level.