Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Flight Plan Route Optimization And Increase The Profit In Airline Industry By Using Hybrid BCF Algorithm


Affiliations
1 School of Computing Science and Engineering, Galgotias University, India
     

   Subscribe/Renew Journal


Airline industry is a booming industry where decisions have to be taken in the dynamic environment. There are many factors which govern the decision-making namely the airline route as considerate amount of profit can be generated by selecting the optimized airline route. The paper proposes a hybrid BCF algorithm which optimizes the flight trajectory and seat allotments. The algorithm specifically optimizes the airline route, seat allotment on a large scale of data set to give the best option to choose in and implement it. The result shows the tremendous variation regarding the net amount there by increasing the profit.

Keywords

Hybrid BCF Algorithm, Decision-Making, Optimized, Airline Route, Profit.
Subscription Login to verify subscription
User
Notifications
Font Size

  • X.S. Yang, “Firefly Algorithm, Stochastic Test Functions and Design Optimisation”, International Journal of BioInspired Computation, Vol. 2, No. 2, pp. 78-84, 2010.
  • X.S. Yang, “Nature-Inspired Metaheuristic Algorithms”, Luniver Press, 2008.
  • X.S. Yang, “Firefly Algorithms for Multimodal Optimization”, Proceedings of International Symposium on Stochastic Algorithms, pp. 169-178, 2009.
  • X.S. Yang, “Biology Derived Algorithms in Engineering Optimization”, Chapter 32, Handbook of Bioinspired Algorithms and Applications, Chapmann & Hall/CRC Press, pp. 589-600, 2005.
  • International Airline Activity-Time Series, Available at: https://bitre.gov.au/publications/ongoing/international_airli ne_activity-time_series.aspx
  • D. Shilane, J. Martikainen, S. Dudoit and S.J. Ovaska, “A General Framework for Statistical Performance Comparison of Evolutionary Computation Algorithms”, Information Sciences, Vol. 178, No. 14, pp. 2870-2879, 2008.
  • Jian Chai, Zhong Yu Zhang, Shou-Yang Wang, Kin Keung Lai and John Liu, “Aviation Fuel Demand Development in China”, Energy Economics, Vol. 46, pp. 224-235, 2014.
  • Olivier Dessens, Marcus O. Kohler, Helen L. Rogers, Rod L. Jones and John A. Pyle, “Aviation and climate change”, Transport Policy, Vol. 34, No. 2, pp. 14-20, 2014.
  • Hideki Fukui and Koki Nagata, “Flight Cancellation as a Reaction to the Tarmac Delay Rule: An Unintended Consequence of Enhanced Passenger Protection”, Economics of Transportation, Vol. 3, No. 1, pp. 29-44, 2014.
  • Shangyao Yan and Ching-Hui Tang, “A Heuristic Approach for Airport Gate Assignments for Stochastic Flight Delays”, European Journal of Operational Research, Vol. 180, No. 2, pp. 547-567, 2007.
  • Christian Kiss-Toth and Gabor Takacs, “A Dynamic Programming Approach for 4D Flight Route Optimization”, Proceedings of IEEE International Conference on Big Data, pp. 24-28, 2014.
  • IBM, “Websphere MQ”, Available at: https://www.ibm.com/support/knowledgecenter/en/SSFKSJ _8.0.0/com.ibm.mq.explorer.doc/e_queues.htm
  • D. Fisher, R. DeLine, M. Czerwinski and S. Drucker, “Interactions with Big Data Analytics”, Interactions, Vol. 13, No. 3, pp. 50-59, 2012.
  • Elton Fernandesa and R.R. Pacheco, “Transport Efficient use of Airport Capacity”, Transportation Research Part A Policy and Practice, Vol. 36, No. 3, pp. 225-238, 2002.
  • X.S. Yang, “A New Metaheuristic Bat-Inspired Algorithm in Nature Inspired Cooperative Strategies for Optimization”, Proceedings of International Conference on Studies in Computational Intelligence, 65-74, 2010.
  • X.S. Yang and S. Deb, “Cuckoo Search via Levy flight”, Proceedings of World Congress on Nature and Biologically Inspired Computing, pp. 210-214, 2009.
  • X.S. Yang, “Bat Algorithm: Literature Review and Applications”, International Journal of Bio-Inspired Computation, Vol. 5, No. 3, pp. 141-149, 2013.
  • X.S. Yang, “Firefly Algorithm, Levy Flights and Global Optimization”, Proceedings of International Conference on Research and Development in Intelligent Systems, pp. 209218, 2010.
  • Gulsah Hancerliogullari, Ghaith Rabadi, Ameer H. AlSalem and Mohamed Kharbeche, “Greedy Algorithms and Metaheuristics for a Multiple Runway Combined Arrival Departure Aircraft Sequencing Problem”, Journal of Air Transport Management, Vol. 32, pp. 39-48, 2013.
  • J.A.D. Atkin, E.K. Burke, J.S. Greenwood and D. Reeson, “A Metaheuristic Approach to Aircraft Departure Scheduling at London Heathrow Airport”, Computer Aided Systems of Public Transport, Vol. 600, pp. 235-252, 2008.
  • Momin Jamil, “A Literature Survey of Benchmark Functions for Global Optimisation Problems”, International Journal on Mathematical Modelling and Numerical Optimisation, Vol. 4, No. 2, pp. 1-12, 2013.
  • Lisa Davison, Clare Littleford and Tim Ryley, “Air Travel Attitudes and Behaviours: The Development of Environment-Based Segments”, Journal of Air Transport Management, Vol. 36, pp. 13-22, 2014.
  • L. Zhe, W.A. Chaovalitwongse, H.C. Huang and E.L. Johnson, “Network Model for Aircraft Routing Problem”, Transportation Science, Vol. 45, No. 1, pp. 109-120, 2011.
  • Y. Suzuki, J.E. Tyworth and R.A. Novack, “Airline Market Share and Customer Service Quality: a ReferenceDependent Model”, Transportation Research Part A: Policy and Practice, Vol. 35, No. 9, pp. 773-788, 2001.
  • S. Ruther, “A Multi-Commodity Flow Formulation for the Integrated Aircraft Routing, Crew Pairing, and Tail Assignment Problem”, Proceedings of 45th Annual Conference of Operations Research Society of New Zealand, pp. 1-6, 2010.
  • E. Kasturi, S. Prasanna Devi, S. Vinu Kiran and S. Manivannan, “Airline Route Profitability Analysis and Optimization using Big Data Analytics on Aviation Data Sets under Heuristic Techniques”, Procedia Computer Science, Vol. 87, pp. 86-92, 2016.

Abstract Views: 200

PDF Views: 0




  • Flight Plan Route Optimization And Increase The Profit In Airline Industry By Using Hybrid BCF Algorithm

Abstract Views: 200  |  PDF Views: 0

Authors

N. V. Kousik
School of Computing Science and Engineering, Galgotias University, India
Tapas Kumar
School of Computing Science and Engineering, Galgotias University, India
C. Rameshkumar
School of Computing Science and Engineering, Galgotias University, India
L. Vetrivendhan
School of Computing Science and Engineering, Galgotias University, India

Abstract


Airline industry is a booming industry where decisions have to be taken in the dynamic environment. There are many factors which govern the decision-making namely the airline route as considerate amount of profit can be generated by selecting the optimized airline route. The paper proposes a hybrid BCF algorithm which optimizes the flight trajectory and seat allotments. The algorithm specifically optimizes the airline route, seat allotment on a large scale of data set to give the best option to choose in and implement it. The result shows the tremendous variation regarding the net amount there by increasing the profit.

Keywords


Hybrid BCF Algorithm, Decision-Making, Optimized, Airline Route, Profit.

References