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A practical model for transfer optimization in a transit network: Model formulations and solutions

Shafahi, Y ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1016/j.tra.2010.03.007
  3. Publisher: 2010
  4. Abstract:
  5. This paper studies the transit network scheduling problem and aims to minimize the waiting time at transfer stations. First, the problem is formulated as a mixed integer programming model that gives the departure times of vehicles in lines so that passengers can transfer between lines at transfer stations with minimum waiting times. Then, the model is expanded to a second model by considering the extra stopping time of vehicles at transfer stations as a new variable set. By calculating the optimal values for these variables, transfers can be better performed. The sizes of the models, compared with the existing models, are small enough that the models can be solved for small- and medium-sized networks using regular MIP solvers, such as CPLEX. Moreover, a genetic algorithm approach is represented to more easily solve larger networks. A simple network is used to describe the models, and a medium-sized, real-life network is used to compare the proposed models with another existing model in the literature. The results demonstrate significant improvement. Finally, a large-scale, real-life network is used as a case study to evaluate the proposed models and the genetic algorithm approach
  6. Keywords:
  7. Transit scheduling ; Departure time ; Genetic algorithm approach ; In-line ; Larger networks ; Mixed integer programming model ; Model formulation ; Optimal values ; Practical model ; Public transportation ; Real-life networks ; Simple networks ; Stopping time ; Transfer coordination ; Transit networks ; Waiting time ; Diesel engines ; Genetic algorithms ; Integer programming ; Mass transportation ; Optimization ; Transfer stations ; Scheduling algorithms ; Genetic algorithm ; Numerical model ; Public transport ; Travel behavior
  8. Source: Transportation Research Part A: Policy and Practice ; Volume 44, Issue 6 , 2010 , Pages 377-389 ; 09658564 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0965856410000467?np=y&npKey=90b1c3dc63930fb3aa1679b8585e86bff140b1b0806e0fca26080e84e6d36131