Using Ant Colony Optimization Algorithm to Solve Airline Crew Scheduling Problems

Authors:
Chih-Chung Lo;Guang-Feng Deng
Affiliations:
Fo Guang University, Taiwan;National Chengchi University, Taiwan
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
Year:
2007

Citing 0
Cited 2

Solving the flight frequency programming problem with particle swarm optimization

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A hybrid meta-heuristic algorithm for optimization of crew scheduling

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, an Ant Colony Optimization (ACO) based Ant Crew Scheduling Model (ACSM) is proposed to solve airline crew scheduling problems. In the proposed ACSM, airline crew scheduling problems are first formulated as traveling salesman problems with flight graph representation. Then, the ACO algorithm is applied to search near-optimal solutions for airline crew schedules. The validity of the proposed ACSM is verified by implementing it in real study cases. The results from the implementation and evaluation confirm that the proposed ACSM is suitable for the airline crew scheduling problems with good performance.