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A Hybrid Multi-Objective and Multi-Criteria Approach to Develop an Assignment Optimization Model in Car Sharing Networks

Mahdaei, Mahdi | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56841 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Akbari Jokar, Mohammad Reza
  7. Abstract:
  8. In this study, given the increasing challenges urban and intercity transportation face in the modern world, including population growth, urban development, and environmental concerns, an innovative approach to optimize the use of car-sharing vehicles is presented. The research aims to develop a multi-objective mathematical programming model for the optimal allocation of car-sharing vehicles, considering key factors such as transportation costs, travel time, and environmental pollution. This seeks to reduce costs, increase efficiency, shorten travel times, and contribute to environmental sustainability. Initially, a thorough literature review was conducted to provide a comprehensive background for the research. Then, using actual travel data from the city of Tehran and necessary preprocessing, the city's regions were classified into eight clusters. This classification aimed to identify the busiest areas to realize the optimal allocation of car-sharing vehicles using the developed mathematical optimization model. This model, which benefits from various multi-objective decision-making approaches, was carefully solved and implemented. Furthermore, in consultation with transportation experts, criteria were prepared for evaluating the performance of the clusters. These criteria were assessed using multi-criteria decision-making methods to provide an accurate ranking of areas for establishing car-sharing stations. The results of this research demonstrate the feasibility of achieving an optimal allocation of car-sharing vehicles, which not only reduces costs and travel time but also plays a significant role in reducing air pollution and enhancing environmental sustainability. This study, leveraging modern data analysis and machine learning methods, charts a new course in optimizing urban and intercity transportation and offers valuable practical insights for designing sustainable transportation systems
  9. Keywords:
  10. Transportation Network ; Multi Objective Programming ; Multicriteria Decision Making ; Mathematical Optimization ; Machine Learning ; Transportation Network Design ; Car-Sharing ; Transportation Allocation Network Design

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