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].
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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
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DOI: https://doi.org/10.1007/978-3-540-30176-9_11
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