Research Topic: Community Research

Community research is conducted in collaboration with public and nonprofit organizations and focused on addressing urban freight, logistics, supply chain, and transportation challenges that have a direct impact on local communities.
These projects involve working closely with these organizations and engaging with the community to develop effective solutions that not only enhance logistics and transportation efficiency but also align with the goals and missions of local entities.

Paper

A Competitive, Charter Air-Service Planning Model for Student Athlete Travel

URL: https://doi.org/10.1016/j.trb.2010.06.002

Publication: Transportation Research Part B: Methodological

Volume: 45 (1)

Pages: 128-149

Publication Date: 2011

Summary:

This paper presents a model for planning an air charter service for pre-scheduled group travel. This model is used to investigate the competitiveness of such an enterprise for student athlete travel in conference sports. The relevant demand subset to be served by a limited charter fleet is identified through a comparison with existing scheduled travel options. Further, the routing and scheduling of the charter aircraft is performed within the same framework. Through this modeling a method for formulating and accommodating continuous time windows and competitive market dynamics in strategic planning for a charter service is developed. Computational improvements to the basic model are also presented and tested. The model is applied to the Big Sky Conference for the 2006–2007 season, quantifying the benefits to the students from such a service and the change in expenditure associated with such a benefit for various assumptions about operations and value of time. The findings indicate the lack of spatial or sport based patterns for maximizing benefit, indicating the absence of simplistic “rules of thumb” for operating such a service, and validating the need for the model.

Authors: Dr. Anne Goodchild, Gautam Gupta, and Mark Hansen

Recommended Citation:
Gautam Gupta, Anne Goodchild, and Mark Hansen (2011). A Competitive, Charter Air-Service Planning Model for Student Athlete Travel. Transportation Research Part B, 45, 128-149.

The Route Machine: An Optimization Framework (Phase 1)

The University of Washington Department of Laboratory Medicine runs 12 routes per day moving lab specimens and conducting departmental business. These routes have been developed over time in an ad hoc fashion.

The Urban Freight Lab will primarily focus on the following objectives for optimization:

Minimize expected lead time (from the time the specimens are ready for pick up to the time they are delivered to the lab for testing)
Minimize the extent to which couriers work outside of their maximum shift durations

The decisions the ‘route machine’ optimization framework ideally should inform:

Day-to-day (operational) decision-making: Given all of the current capacities (i.e., number of vehicles) can routes be improved through changing order of routes or destinations serviced in route?
Tactical decision-making: What modifications to the current capacities (i.e., increasing the number of vehicles) will produce the greatest benefit? How will the optimal routes change if there are modifications to customer requirements?
Strategic decision-making: If UW Medicine Department of Laboratory Medicine expands its operations how will routes and capacities need to change to accommodate the new situation? What should the workforce balance between full-time workers and contractors look like?

This analysis includes:

Phase 1: Evaluate the existing routes on a qualitative basis to judge whether there is sufficient opportunity for improvement, and strategies that show greatest opportunity for improvement
Phase 1: Conduct an inventory of off the shelf tools and determine their suitability for the application
Phase 2: Build the Route Machine tool, either using off-the shelf software tools, building the tool from scratch, or some combination of the two.