Simulation-Based Optimization for Resource Allocation Problem in Finite-Source Queue with Heterogeneous Repair Facility

The paper deals with an optimal allocation problem in a finite-source queueing system where the repair facility consists of multiple heterogeneous servers. We use both the reinforcement learning methods and the random search method based on simulated annealing to solve the discrete optimization problem. Experimental results are compared with an actual solution obtained by policy iteration of the dynamic programming. The advantages and disadvantages of the methods and the peculiarities of their use for controllable queueing system are discussed.