A representational paradigm for dynamic resource transformation problems

This paper offers a new vocabulary for representing complex problems in a stochastic, dynamic setting. Our focus is on operational problems that need to be solved under uncertainty, and complex problems which are difficult to formulate mathematically in a clear and elegant way. We believe that similarities between problems are often disguised by semantic differences that reflect the contextual domain of an application. It is not readily apparent, for example, that the blocking problem of railroads and the load planning problem of less-than-truckload trucking are both instances of a dynamic service network design problem. The question that tends to arise is: when are apparently different problems similar, and when are seemingly similar problems different?