Abstract
This study presents a technique for reducing the bias induced by arbitrary initial conditions in some discrete simulation studies. The technique relies on compensating the existing bias in a run by purposely introducing a deviation in the counter-direction during the subsequent run. Specifically, after obtaining a sample with initial condition X0, an antithetic companion run is generated starting from (2X - X0). This introduces an adjustment equal and opposite to the indicated deviation, as measured by the distance between the current sample mean X and the initial condition X0. Then the overall mean has a significantly lower bias. Application of the technique to first-order autoregressive process and to a machine-repair system revealed that it is capable of reducing, and in most cases practically removing, the transient effects within moderate sample sizes.
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