American Society of Civil Engineers


Airline Network Revenue Management Based on Simulated Annealing Genetic Algorithm


by Bing Dong, (School of Traffic and Transportation, Southwest Jiaotong University Chengdu, Sichuan, 610031, China; and School of Computer, Civil Aviation Flight University of China Ganghan, Sichuan, 618307, China. E-mail: dbcafuc@126.com), Wen Du, (School of Traffic and Transportation, Southwest Jiaotong University Chengdu, Sichuan, 610031, China), and Lianming Zhao, (School of Traffic and Transportation, Southwest Jiaotong University Chengdu, Sichuan, 610031, China)
Section: Volume IV - System Optimization and Simulation Models, pp. 2790-2796, (doi:  http://dx.doi.org/10.1061/41139(387)391)

Note: Acknowledgment: This work is supported by grant 60776820 of the Chinese National Science Foundation. Work partially supported by grant J2008-76 of the CAFUC Nature Science Foundation.

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Document type: Conference Proceeding Paper
Part of: ICLEM 2010: Logistics For Sustained Economic Development: Infrastructure, Information, Integration
Abstract: This paper develops a network revenue management model which incorporates random programming models using simulated annealing genetic algorithm. The model is designed to accommodate a number of realistic assumptions for multi-leg or network problems. Under the assumptions, the model can provide an optimal booking strategy for the airline industry and the simulated annealing genetic algorithm can give a better result than other optimization method such as Lagrange relaxation and Scenario decomposition method for which a numerical example is given. The computational results indicate that the model and solving method are feasible and effective.


ASCE Subject Headings:
Airlines
Revenues
Algorithms
Logistics