Simulation model for a vanpooling system
Computers and Industrial Engineering
Efficient algorithms for the capacitated concentrator location problem
Computers and Operations Research
Hierarchial concentrator location problem
Computer Communications
A distributed geographic information system for the daily car pooling problem
Computers and Operations Research
Siting park-and-ride facilities using a multi-objective spatial optimization model
Computers and Operations Research
Heuristic algorithms for solving the interval flow transshipment network
Heuristic algorithms for solving the interval flow transshipment network
The Dynamic Uncapacitated Hub Location Problem
Transportation Science
Benders Decomposition for Large-Scale Uncapacitated Hub Location
Operations Research
Hi-index | 0.00 |
We present optimization models and solution algorithms for the Vanpool Assignment Problem. A vanpool is typically a group of 9-15 passengers who share their commute to a common target location (typically an office building or corporate campus). Commuters in a vanpool drive from their homes to a park-and-ride location where they board a van and ride together to the target location; at the end of the work day they ride together back to the park-and-ride location. The Minimum Cost Vanpool Assignment Model (MCVAM) developed in this study is motivated by a program offered by Gulfstream Aerospace, a large employer in the Dallas/Fort-Worth area, Dallas Area Rapid Transit (DART), and Enterprise Rent-A-Car. Our MCVAM imposes constraints on the capacity of each van and quality-of-service constraints on the cost and travel time involved in joining a vanpool. The goal of the MCVAM is to minimize the total cost of a one-way trip to the target location for all employees (including those employees who opt-out of the program and choose not to join a vanpool). To the best of our knowledge, this is the first mathematical programming model proposed for the standard (one-stop) Vanpool Assignment Problem. The MCVAM models the current practice in vanpooling of using one park-and-ride location per vanpool. We also present a Two-Stop MCVAM (TSMCVAM) that offers significant cost savings compared to the MCVAM with little or no increase in trip times for most passengers by allowing vanpools to stop at a second park-and-ride location. We present heuristics for the TSMCVAM which are shown in a computational study to find solutions with optimality gaps ranging from 5% to 10% in CPU times ranging from 1 to 15min for problem instances with up to 600 employees and 120 potential park-and-ride locations.