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Investigating Effects of Urban Freight Companies' Scale on their Transport Efficiency and Developing a Tool for Integration of Freight Companies

Dashti, Mohammad Mahdi | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55548 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Samimi, Amir; Kermanshah, Amir Hassan
  7. Abstract:
  8. In this research, a dashboard has been developed to support decision-making in the integration of freight companies. Freight companies usually consist of a limited number of vehicles due to the high cost of vehicles, while the fixed costs of a freight company constitute a significant part of that company's total cost. Therefore, if these companies are merged, their total cost will be substantially decreased. Moreover, under particular demand levels, the integration of freight companies reduces the mileage, travel time, and the number of required cars. Therefore, the integration of freight companies not only reduces fixed costs but also reduces other costs including greenhouse gas costs by optimizing the route planning process and reducing mileage. Despite the linear status of the vehicle routing problems, these problems are placed in the category of hard problems because of the exponential increase of the possible solution space, which cannot be solved by usual methods. Therefore, to solve these types of problems in real conditions, it is necessary to utilize meta-heuristic methods. This research uses the genetic algorithm and the simulated annealing algorithm to solve the vehicle routing problem. This research consists of two main modules, in the first module, a proactive dashboard is developed using R to support decision-making for the integeration of freight companies. This dashboard receives the amount and location of each demand, then solves the vehicle routing problem with the aforementioned algorithms. In addition, it calculates the number of required vehicles, the optimal route, and its travel time. In the last module, firstly all costs of a freight company are extracted from the literature; subsequently, by defining various scenarios, the integration of freight companies will be investigated from different dimensions is investigated using the dashboard developed in the first module. Eventually, plans and strategies will be presented to attract freight companies to the integration program, considering that freight company integration is not an appropriate decision in all circumstances.
  9. Keywords:
  10. Vehicle Routing Problem ; Genetic Algorithm ; Heuristic Algorithm ; Optimization ; Pickup and Delivery Problem Optimization ; Efficiency ; Simulated Annealing Method ; Road Freight

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