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Optimizing urban bike-sharing systems: a stochastic mathematical model for infrastructure planning.

Seyedeh Asra Ahmadi1, Peiman Ghasemi2, Jan Fabian Ehmke3

  • 1Department of Logistics, Tourism and Service Management, German University of Technology in Oman, Muscat, Oman.

Central European Journal of Operations Research
|January 12, 2026
PubMed
Summary

This study optimizes bike-sharing systems using a stochastic model for dynamic demand, improving resource allocation and infrastructure planning. Effective cost management is key to meeting user travel needs efficiently.

Keywords:
Bike-sharing systemsChance constraint modelPeak and non-peak periodsStochastic mathematical model

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Area of Science:

  • Operations Research
  • Transportation Science
  • Urban Planning

Background:

  • Bike-sharing systems face challenges with dynamic demand, exacerbated by events like the COVID-19 pandemic.
  • Optimizing resource allocation and infrastructure is crucial for efficient bike-sharing operations.

Purpose of the Study:

  • To develop a stochastic mathematical model for optimizing bike-sharing system resource allocation and infrastructure planning.
  • To enhance system performance and resource utilization under varying demand scenarios.
  • To ensure total travel demand fulfillment and assess network capacity.

Main Methods:

  • Development of a stochastic mathematical model for bike-sharing station allocation and network design.
  • Application of the model to the Vienna bike-sharing system for a case study.
  • Conducting sensitivity analysis on cost parameters.

Main Results:

  • The stochastic model effectively optimizes resource allocation and infrastructure planning for bike-sharing systems.
  • Case study in Vienna demonstrates practical applicability and potential for improved efficiency and service quality.
  • Sensitivity analysis indicates that increased costs for docks and stations negatively impact fulfilled demand.

Conclusions:

  • The proposed stochastic model provides a robust framework for bike-sharing system optimization.
  • Cost-effective infrastructure planning is essential for maximizing service provision and user satisfaction.
  • The model offers valuable insights for enhancing the resilience and efficiency of urban mobility solutions.