2989. Risk-Aware Car Sharing: Ensuring Fairness and Service Quality with Substitution
Invited abstract in session WB-30: Shared Mobility Optimization III, stream Shared Mobility Optimization.
Wednesday, 10:30-12:00Room: Maurice Keyworth 1.05
Authors (first author is the speaker)
| 1. | Esra Koca
|
| Industrial Engineering, Sabanci University | |
| 2. | Beste Basciftci
|
| Business Analytics, University of Iowa |
Abstract
In today's competitive car-sharing industry, optimizing operations while ensuring high-quality service and fairness is crucial for efficiency, profitability, and market competitiveness. This paper examines a reservation-based car-sharing company offering round-trip and one-way rentals with a mixed fleet. We address strategic fleet positioning, relocation, and operational decisions, including vehicle allocation and routing, under demand uncertainty. Our model incorporates risk-aware constraints to ensure fairness across customer segments and demand points while maintaining customer satisfaction. We introduce a stochastic optimization framework that accounts for uncertain demand realizations and integrates substitution options to improve resource utilization. By considering both risk-aware quality of service and fairness constraints, our approach enhances decision-making under uncertainty. To solve this problem efficiently, we propose a decomposition-based branch-and-cut algorithm using the L-Shaped method. This enables us to handle large-scale instances while maintaining computational efficiency. Our computational study demonstrates the effectiveness of our approach in balancing service quality, fairness, and operational efficiency under market uncertainties, offering valuable insights for decision-makers in car-sharing operations.
Keywords
- Programming, Stochastic
- Service Operations
- Transportation
Status: accepted
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