published journal article
published journal article
published journal article
published journal article
AbstractThe ability to fold and deploy lightweight composites without damage makes them attractive for aerospace applications. However, one of the challenges faced with deployable composites is their high stiffness, which results in a relatively high …
published journal article
working paper
Linear and nonlinear multivariate statistical analyses are applied to determine how the types of accidents that occur on heavily used freeways in Southern California are related both to the flow of traffic and to weather and ambient lighting conditions. Traffic flow is measured in terms of time series of 30-second observations from inductive loop detectors in the vicinity of the accident prior to the time of its occurrence. Results indicate that the type of collision is strongly related to median traffic speed and to temporal variations in speed in the left and interior lanes. Hit-object collisions and collisions involving multiple vehicles that are associated with lane-change maneuvers are more likely to occur on wet roads, while rear-end collisions are more likely to occur on dry roads during daylight. Controlling for weather and lighting conditions, there is evidence that accident severity is influenced more by volume than by speed.
research report |
Dec 2001
published journal article |
Jul 2003
published journal article
Phd Dissertation
Because of the growing importance of hub-and-spoke operations in the trucking industry, crossdocking has become an important and effective tool to transfer freight. Companies like Wal-Mart, Costco and Home Depot are using this kind of facility in their logistics operations. In these crossdocks, efficiently operating them, thereby reducing unnecessary waiting and staging congestion for freight and workers is an important issue for managers. This dissertation uses real-time information about the contents of inbound and outbound trailers and the locations of pallets to schedule unloading for waiting trailers or assign destinations for unloading pallets: we choose a waiting trailer that will need the least time for its pallets and existing pallets; and we may assign an alternate destination for a pallet if its primary destination is expected to encounter congestion. Two dynamic trailer scheduling and four alternate destination strategies are proposed and compared with baseline scenarios. Our simulation results suggest that: (1) Our strategies are effective. The two time-based trailer scheduling algorithms can save cycle times as much as 64%, 57% and 30% in the 4-to-4, 4-to-8 and 8-to-8 crossdock scenarios, respectively; the four alternate destination strategies can save cycle times as much as 34% in the 8-to-8 staging crossdock scenarios. In addition, these strategies can raise throughputs for crossdocks. These effects should result in noticeable improvements in supply chain networks, including shorter transportation lead-times, more reliable on-time deliveries and lower inventory costs. (2) In our alternate destination strategies, even if a destination-change results in extra time for value-added services for freight, the strategies are still worth adopting. (3) The combination models of our trailer scheduling algorithms and alternate destination strategies work better than solely implementing an alternate destination strategy when trailer arrivals are dense. (4) A higher flexibility in choosing alternate destinations can bring higher performance for crossdocks.
Phd Dissertation
Strategies, models, and algorithms facilitating such models are explored to provide transportation network managers and planners with more flexibility under uncertainty. Network design problems with non-stationary stochastic OD demand are formulated as real option investment problems and dynamic programming solution methodologies are used to obtain the value of flexibility to defer and re-design a network. The design premium is shown to reflect the opportunity cost of committing to a “preferred alternative” in transportation planning. Both network option and link option design problems are proposed with solution algorithms and tested on the classical Sioux Falls, SD network. Results indicate that allowing individual links to be deferred can have significant option value. A resource relocation model using non-stationary stochastic variables as chance constraints is proposed. The model is applied to air tanker relocation for initial attack of wildfires in California, and results show that the flexibility to switch locations with non-stationary stochastic variables providing 3-day or 7-day forecasts is more cost-effective than relocations without forecasting. Due to the computational costs of these more complex network models, a faster converging heuristic based on radial basis functions is evaluated for continuous network design problems for the Anaheim, CA network with a 31-dimensional decision variable. The algorithm is further modified and then proven to converge for multi-objective problems. Compared to other popular multi-objective solution algorithms in the literature such as the genetic algorithm, the proposed multi-objective radial basis function algorithm is shown to be most effective. The algorithm is applied to a flexible robust toll pricing problem, where toll pricing is proposed as a strategy to manage network robustness over multiple regimes of link capacity uncertainty. A link degradation simulation model is proposed that uses multivariate Bernoulli random variables to simulate correlated link failures. The solution to a multi-objective mean-variance toll pricing problem is obtained for the Sioux Falls network under low and high probability seasons, showing that the flexibility to adapt the Pareto set of toll solutions to changes in regime—e.g. hurricane seasons, security threat levels, etc.—can increase value in terms of an epsilon indicator.
published journal article