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Flight Frequency Determination and Aircraft Routing Problem: Model and Solution

Nasr Isfahani, Hossein | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48427 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shafahi, Yusof
  7. Abstract:
  8. This study aims to solve weekly Flight Frequency Determination and Aircraft Maintenance Routing Problem (AMRP) simultaneously. The objective function here is to maximize the total net profit of an assumptive airline with predetermined airfare and origin-destination market demand. All the needed constraints regarding AMRP is added to the modified version of original model which proposed by Ghafoori in 2011. On the other hand, while this kind of model is based on travelling salesman problem, the occurrence of sub-tours is inevitable. Thus, the model will be, secondly, restricted with more constraints which help eliminate infeasible solutions. The proposed model, then, is tested for three different networks, two small-sized, and one medium-sized networks for 1-day horizon, using CPLEX/GAMS. A comparison, then, is made between the result of proposed model and Ghafoori’s. It proves that not only are the outcomes of the model practical and significantly improved in the matter of net profit, but also the calculation time is, in some cases, much lesser than that of the Ghafoori’s model. Afterward, the model will be solved for a weekly horizon. In the face of the fact that traveling salesman problem is NP-hard, the model cannot be solved with commercial programs for medium and real sized networks. Therefore, a heuristic method based on Genetic Algorithm is proposed to solve the model for these kinds of networks. In this algorithm Partially Matched Crossover is modified to suit the nature of the problem. Additionally, mutation algorithm is designed to cover all the possible scenarios of enhancing the objective function. The result shows that the proposed algorithm can solve the model efficiently and precisely
  9. Keywords:
  10. Air Transportation Networks ; Genetic Algorithm ; Flight Frequency Determination ; Optimization ; Mixed Integer Programming

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