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An Optimization Model for Shared Electric Vehicle Routing Problem in Urban Trips

Safari Taherkhani, Mohammad | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54168 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shafahi, Yousef
  7. Abstract:
  8. In today’s world, people’s tendency to use their own vehicles is relatively high since private cars provide more convenience, better safety, and better time management than public transportation, but cause more traffic in the streets. Ride-sharing is one of the management tools that has attracted a lot of attention in recent years to mitigate the traffic congestion. Also, electric vehicles are used for public transportation in many parts of the world to achieve a sustainable environment. In this study, we assume that passengers’ origin, destination, and preferred time windows for pick-up and drop-off are known in advance. The aim of the study is to determine the sequence of visiting travel requests by each vehicle to minimize the cost of operating a ride-sharing system with a fleet of electric vehicles; the study covered most of the operational constraints that exist in the real-world for electric vehicles such as battery management of the fleet, partial recharge time, the nonlinear charging function, and the possible queue time at recharging stations, alongside the typical constraints of ride-sharing systems. The problem is formulated as a mixed-integer linear program, and a genetic algorithm is used to find near optimum solutions for large instances. Computational experiments are performed based on real data from the Shiraz city origin-destination survey in order to find minimum cost routes and understand the impacts of shared vehicles on vehicle miles traveled (VMT) and passengers’ total travel time. Results show that using ride-sharing services may lead to an increase in VMT up to 141 percent. And with 88 percent decrease in the number of vehicles in the network, a ride-sharing system can give service to its passengers with an average time windows violation of 2.781 minutes
  9. Keywords:
  10. Mixed Integer Linear Programming ; Genetic Algorithm ; Optimization ; Electric Motor Vehicles ; Vehicle Routing Problem ; Town Trip ; Ride-Sharing System

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