Abstract
Airline crew scheduling is a very visible and economically significant problem faced by airline industry. Set partitioning problem (SPP) is a role model to represent & solve airline crew scheduling problem. SPP itself is highly constrained combinatorial optimization problem so no algorithm solves it in polynomial time. In this paper we present a genetic algorithm (GA) using new Cost-based Uniform Crossover (CUC) for solving set partitioning problem efficiently. CUC uses cost of the column information for generating offspring. Performance of GA using CUC is evaluated using 28 real-world airline crew scheduling problems and results are compared with well-known IP optimal solutions & Levine’s GA solutions [13].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balas, E., Padberg, M.: On the set-covering problem: II. an algorithm for set partitioning. Operations Research 23, 1152–1161 (1975)
Beasley, J., Chu, P.: A genetic algorithm for the set partitioning problem. Technical report, Imperial College, The Management School, London (1995)
Beasley, J.E.: Or-library: distributing test problems by electronic mail. Journal of the Operational Research Society 41(11), 1069–1072 (1990)
Czech, Z.J.: Parallel simulated annealing for the set-partitioning problem. In: Proc. of the 8th Euromicro Workshop on Parallel and Distributed Processing, Rhodos, Greece, January 2000, pp. 343–350 (2000)
Bull, D.R., Beasley, D., Martin, R.R.: An overview of genetic algorithms: Part 2, research topics. University Computing 15(4), 170–181 (1993)
Dolan, E.D., More, J.J.: Benchmarking optimization software with performance profiles. Mathematical Programming Online (October 2001)
Fisher, M.L., Kedia, P.: Optimal solutions of set covering/partitioning problems using dual heuristics. Management Science 36, 674–688 (1990)
Gen, M., Cheng, R.: Genetic Algorithms and Engineering Optimization. In: Engineering Design and Automation, Wiley Interscience Publication, John Wiley & Sons. Inc., New York (2000)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addision-Wesley, Reading (1989)
Harche, F., Thompson, G.L.: The column substraction algorithm: An exact method for solving the weighted set covering problem. Computers and Operations Research 21(6), 689–705 (1994)
Hoffman, K.L., Padberg, M.: Solving airline crew scheduling problems by branch and cut. Management Science 39, 657–682 (1993)
Holland, J.H.: Adaptation in Natural and Artificial Systems, 2nd edn. MIT Press, Cambridge (1992)
Levine, D.: A Parallel Genetic Algorithm for the Set Partitioning Problem. Technical Report ANL-94/23 (May 1994)
Levine, D.: Application of a hybrid genetic algorithm to airline crew scheduling. Computers and Operations Research 23(6), 547–558 (1996)
Tanga, R., Anbil, R., Johnson, E.L.: A global approach to crew-pairing optimization. IBM Systems Journal 31(1), 71–78 (1992)
Fogel, D., Back, T., Michalewicz, Z., Pidgeon, S. (eds.): Handbook of Evolutionary Computation. Oxford University Press, Oxford (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kotecha, K., Sanghani, G., Gambhava, N. (2004). Genetic Algorithm for Airline Crew Scheduling Problem Using Cost-Based Uniform Crossover. In: Manandhar, S., Austin, J., Desai, U., Oyanagi, Y., Talukder, A.K. (eds) Applied Computing. AACC 2004. Lecture Notes in Computer Science, vol 3285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30176-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-30176-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23659-7
Online ISBN: 978-3-540-30176-9
eBook Packages: Springer Book Archive