抄録
The paper presents a simple, efficient approach of
formulating and optimizing the global Airline Crew Scheduling Problem (ACSP). Both the tasks of plane and crew assignment are addressed simultaneously using Discrete Particle Swarm Optimization (DPSO). Realistic constraints are conceptualized and incorporated. Simulation is performed for a simple test case and a more complex one. Importance of adopting explicit diversity preservation techniques, advantages of constraining the search space as well as the effects of DPSO on different aspects of ACSP are explored. Analysis and discussions provide a more holistic understanding of the complexity involved in ACSP and new insights into effective ways of improving the results. The overall findings indicate that DPSO is a potential candidate for solving more complex extensions of the ACSP.
