Before revision: In simulation-based optimization of queuing systems, the presence of discrete-valued parameters (such as buffer sizes and the number of servers) makes the optimization difficult. We propose a novel technique for embedding such discrete parameters into a continuous space, so that optimization can be performed efficiently using continuous-space methods . Unlike spatial interpolation, our embedding technique is based on a randomization of the simulation model .
After revision: Motivated by the problem of discrete-parameter simulation optimization (DPSO) of queueing systems, we consider the problem of embedding the discrete parameter space into a continuous space, so that optimization can be performed efficiently using continuous-space methods . Unlike spatial interpolation, our embedding technique is based on a randomization of the simulation model .