Online OR models have been the subject of increased attention in recent years with the rapid expansion of the Internet. Although much has been written about the implementation, as well as the formal analysis of online models, little has been said about how to handle uncertainty in an online setting. In particular, the dynamic nature of uncertainty that is so characteristic of online models, where estimates and distributions evolve in parallel with the state of the model, has been largely ignored. In this paper, we present a new representation for uncertainty in online models. This representation is object-oriented and, as such, provides several important software-engineering advantages over traditional representations for uncertainty. Moreover, by using the event listener paradigm it provides an explicit mechanism for handling dynamic uncertainty in an elegant and extensible manner. A series of computational experiments demonstrates that there is no significant overhead to our representation when compared to traditional representations on a realistic application and, in some cases, our representation can be noticeably faster. (.
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Management Science and Operations Research
- Philosophy of Modeling