Building knowledge to improve enterprise performance from inventory simulation models

This paper describes the process of building knowledge to improve enterprise performance. This allows managers both to identify unknown risks and to develop solutions that mitigate these risks. One of the most critical risks that the enterprise faces involves the unidentified presence of serial-correlation components on the demand patterns. Depending upon the levels of such correlation, inventory control policies can be appreciably inaccurate. We propose to use a knowledge management portfolio that allows managers to capture and build knowledge from their complex systems. We find that the error generated from ignoring identified risk factors exponentially grows as the autocorrelation increases. We construct an enhanced simulated annealing algorithm that provides superior solutions to this type of problem.