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EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

Author

Listed:
  • Yaser Rouzpeykar
  • Roya Soltani
  • Mohammad Ali Afashr Kazemi

Abstract

The aviation industry is one of the most widely used applications in transportation. Due to the limited capacity of aircraft, revenue management in this industry is of high significance. On the other hand, the hub location problem has been considered to facilitate the demands assignment to hubs. This paper presents an integrated p‐hub location and revenue management problem under uncertain demand to maximize net revenue and minimize total cost, including hub establishment and transportation costs. A fuzzy programming model and a genetic algorithm are developed to solve the proposed model with different sizes. The mining and petroleum industry is used for case studies. Results show that the proposed algorithm can obtain a suitable solution in a reasonable amount of time.

Suggested Citation

  • Yaser Rouzpeykar & Roya Soltani & Mohammad Ali Afashr Kazemi, 2022. "EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:7801188
    DOI: 10.1155/2022/7801188
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    References listed on IDEAS

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    2. Demet Çetiner, 2013. "Fair Revenue Sharing Mechanisms for Strategic Passenger Airline Alliances," Lecture Notes in Economics and Mathematical Systems, Springer, edition 127, number 978-3-642-35822-7, December.
    3. Taherkhani, Gita & Alumur, Sibel A., 2019. "Profit maximizing hub location problems," Omega, Elsevier, vol. 86(C), pages 1-15.
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