The goal of this research is to extend the method of infinitesimal perturbation analysis (IPA) to large new classes of discrete-event dynamic systems (DEDS), and thus make it a practical tool for analysis and control of DEDS. The current consensus of the research community is that IPA is an effective tool, but quite limited in the range of systems to which it can be applied. For example, it is generally inapplicable to systems with multiple classes of customers or systems with finite-capacity buffers. But these features are central in many applications. Thus IPA is widely regarded as an interesting technique, but not practically useful. We claim that this is incorrect and that IPA can be applied quite generally. We have developed theoretical support for this claim; the purpose of this research is to translate this theory into a practical "machinery" for implementing IPA. Our approach is based on constructing continuous measure-changing mappings on the sample path space using an appropriate representation (construction) of the process. A key element is that we require continuity only for the performance measure of interest, rather than an entire class of performance measures. This allows a substantial weakening of the existing conditions for the applicability of IPA. The success of this research will represent a breakthrough in the performance- oriented analysis and control of DEDS, and contribute substantially toward practical success in this area.
