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Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability
Mohammad-Reza Namazi-Rad1, Michelle Dunbar2, Hadi Ghaderi3
1SMART Infrastructure Facility, University of Wollongong, Wollongong, NSW 2522, Australia; National Institute for Applied Statistics Research Australia, University of Wollongong, Wollongong, NSW 2522, Australia.
Plos One
|May 21, 2015
Summary
This study introduces a framework to optimize transport transit times, balancing punctuality and profitability. It helps planners make data-driven decisions for improved service quality and operational efficiency.
Area of Science:
- Operations Research
- Transportation Science
- Logistics Management
Background:
- Improving transport service reliability and reducing transit times are critical for service quality and profitability.
- Understanding network-specific factors influencing transit time and their cost-benefit is essential for transport planners.
Purpose of the Study:
- To develop a framework for evaluating proposed changes to average transit time.
- To determine optimal average arrival times that balance punctuality levels with minimized operational costs.
Main Methods:
- Modeling transit-time variability using a truncated probability density function.
- Comparing potential gains against increased service costs using general cost-benefit functions.
- Formulating the problem as a constrained optimization problem.
Main Results:
- The framework allows for the evaluation of trade-offs between transit time reduction, punctuality, and operational costs.
- Optimal average transit times can be identified to enhance service punctuality while ensuring cost-benefit.
Conclusions:
- The proposed framework aids transport planners in optimizing transit operations.
- Balancing transit time, punctuality, and cost-benefit is achievable through constrained optimization.
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