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This paper addresses the Vehicle Relocation Problem (VReP) in free-floating car-sharing systems, focusing on real-time strategies to address demand-supply imbalances. We propose a solution combining AI-based demand and vehicle availability prediction with decision-making algorithms for staff-assisted relocations. Using data from Kraków, Poland, the service area is divided into zones to enable discrete optimization. Experiments with multiple algorithms show significant improvements in fleet management over non-optimized approaches. The results demonstrate the value of predictive models in improving the efficiency and competitiveness of car-sharing systems.

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Decision Making on Vehicles Relocations in Free-Flotation Car-Sharing Schemes

  • 会议论文

  • 发表日期：

    2026年

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  • Pawel Skrzynski,
  • Piotr Szwed,
  • Jaroslaw Was

摘要

This paper addresses the Vehicle Relocation Problem (VReP) in free-floating car-sharing systems, focusing on real-time strategies to address demand-supply imbalances. We propose a solution combining AI-based demand and vehicle availability prediction with decision-making algorithms for staff-assisted relocations. Using data from Kraków, Poland, the service area is divided into zones to enable discrete optimization. Experiments with multiple algorithms show significant improvements in fleet management over non-optimized approaches. The results demonstrate the value of predictive models in improving the efficiency and competitiveness of car-sharing systems.