Showing papers by "L. Jeff Hong published in 2006"

Discrete Optimization via Simulation Using COMPASS

Abstract: We propose an optimization-via-simulation algorithm, called COMPASS, for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables are integer ordered. We prove that COMPASS converges to the set of local optimal solutions with probability 1 for both terminating and steady-state simulation, and for both fully constrained problems and partially constrained or unconstrained problems under mild conditions.

Fully Sequential Indifference-Zone Selection Procedures with Variance-Dependent Sampling

Abstract: Fully sequential indifference-zone selection procedures have been proposed in the simulation literature to select the system with the best mean performance from a group of simulated systems. However, the existing sequential indifference-zone procedures allocate an equal number of samples to the two systems in comparison even if their variances are drastically different. In this paper we propose new fully sequential indifference-zone procedures that allocate samples according to the variances. We show that the procedures work better than several existing sequential indifference-zone procedures when variances of the systems are different. © 2006 Wiley Periodicals, Inc. Naval Research Logistics 53: 464-476, 2006