Optimizing Fleet Composition and Size under Uncertainty in Urban Transit Systems

The goal of this project was to study the fleet sizing problem in the context of an urban transit system with several unique features: (1) a fleet with a heterogeneous mixture of vehicles; (2) integrated decision support, including acquisition, retirement, and allocation decisions over multiple time periods; and (3) various uncertainties regarding demand for origin-destination (OD) pairs and vehicle efficiency. Over the course of a one-year grant effort, the researchers first developed a deterministic optimization model to minimize the total fleet acquisition and operation costs for all time periods within the planning horizon. Then, a two-stage stochastic programming (SP) model was devised to explicitly cope with uncertainty. The model minimizes the expected total costs by optimizing (1) the here-and-now fleet acquisition and retirement decisions in the first stage and (2) the allocation recourse decisions in the second stage after the random parameters are realized. The research team collaborated with a local third-party logistics (3PL) company in St. Louis, Missouri, who provided real-world data for this project. Computational studies were conducted to show the benefit of the two-stage SP model by comparing it to the deterministic model using point estimates of random parameters.

Record URL:
Record URL:

Language

English

Project

Status: Completed
Funding: $45000
Contract Numbers:
DTRT13-G-UTC37
Sponsor Organizations:
Midwest Transportation Center

Iowa State University
2711 S Loop Drive, Suite 4700
Ames, IA United States 50010-8664

University of Missouri, St. Louis

1 University Boulevard
St. Louis, MO United States 63121-4400

USDOT/OST-R

Washington DC, United States

Office of the Assistant Secretary for Research and Technology

University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590
Managing Organizations:
Midwest Transportation Center

Iowa State University
2711 S Loop Drive, Suite 4700
Ames, IA United States 50010-8664
Performing Organizations:
University of Missouri, St. Louis

1 University Boulevard
St. Louis, MO United States 63121-4400
Principal Investigators:
Li, Haitao
Start Date: 20160101
Expected Completion Date: 20180131
Actual Completion Date: 0

Subject/Index Terms

TRT Terms: Bus transit operations; Demand; Fleet management; Freight and passenger traffic; Logistics; Operating costs; Optimization; Paratransit services; Stochastic processes; Third party logistics providers; Transit operating agencies; Transit operators; Travel time; Uncertainty; Urban transit
Geographic Terms: Saint Louis (Missouri)
Subject Areas: Finance; Freight Transportation; Operations and Traffic Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

Accession Number: 01594544
Record Type: Research project
Source Agency: Midwest Transportation Center
Contract Numbers: DTRT13-G-UTC37
Files: UTC, RIP
Created Date: Mar 24 2016 3:32PM