Navigating Uncertainty: A Framework for Optimising Public Transport Networks’ Performance

Gang Lin, Honglei Xu, Shaoli Wang (), Conghua Lin, Fan Zhang and Junxiang Zhu
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Gang Lin: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia
Honglei Xu: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia
Shaoli Wang: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia
Conghua Lin: School of Architecture and Planning, Fujian University of Technology, Fuzhou 350118, China
Fan Zhang: Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
Junxiang Zhu: School of Design and Built Environment, Curtin University, Perth, WA 6102, Australia

Sustainability, 2024, vol. 16, issue 3, 1-24

Abstract: Public transport (PT) networks face significant challenges in achieving optimal outcomes due to the presence of risk and uncertainty. Despite the importance of optimising PT networks’ performance, limited research has applied risk management tools to tackle this issue. In response, this study presents a three-stage framework to optimise PT networks’ performance in uncertain conditions. First, we establish a PT criteria matrix using an analytic hierarchy process to develop a criteria model and calculate the criteria weightings. Second, we propose a multi-aspiration-level goal programming approach to optimise a PT network’s performance based on the weighted results. To manage uncertainty, we use Monte Carlo simulation to analyse the probability of the optimal solution. Finally, to validate our approach, we apply the three-stage framework to three case study areas in Australia. The results of this research offer significant insights into identifying the likelihood of criteria optimisation scenarios, thereby assisting decision makers in allocating resources for optimising the delivery of PT network performance solutions in accordance with government requirements.

Keywords: uncertainty; public transport network optimisation; three-stage model; sampling; multiple-criteria decision making (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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