Trip Assignment under Energy and Environmental Constraints
Limits on available energy and allowable environmental impacts may soon restrict transportation systems. Relatively little work has been done to investigate how this will impact the techniques used in the eld of transportation engineering. This research considers one such technique, all-or-nothing trip assignment. A process that today involves solving thousands of shortest path problems may involve solv- ing thousands of constrained shortest path problems in the future. This research examines the impact such a shift will have on computational burdens. The results of computational studies involving energy-constrained trip assign- ment are presented here. It is found that solving constrained shortest path problems can take several orders of magnitude more time than solving traditional shortest path problems. This is worrying given that such problems will have to be solved large numbers of time in order to use one of the simplest techniques of transportation en- gineering. A specialized algorithm (Carlyle and Wood 2003) typically outperforms a generic solver, but occasionally takes an excessively long amount of time to select a path. The results indicate that it may become increasingly important for trans- portation engineers to be well versed in optimization.