A comparison of multiple linear regression approaches for fitting clearing functions to empirical data

We examine the problem of estimating clearing functions (CFs) that describe the expected output of a production resource as a function of its expected workload from empirical data. We use a simulation model of a scaled-down wafer fabrication facility to generate the data and evaluate the performance of the resulting CFs. We compare the performance of production plans generated using load based and product based CFs and find that using load based CFs yields better performance.