A new mathematical model to cover crew pairing and rostering problems simultaneously

Crew scheduling problem includes two separate subproblems, namely, crew pairing and crew rostering problems. Solving these two subproblems in a sequential order may not lead to an optimal solution. This study includes two main novelties. It combines these two subproblems and presents them in a single model. On the other hand, despite previous researches that considered a pairing continuously, the proposed model benefits from the capability of considering one or more days off in a pairing assigned to a crew member. This is extremely useful as it enables the crew to participate in required courses, doing medical checks, etc. Two solution approaches, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), are used to solve the model. Eventually, the performance of the proposed algorithms is evaluated. Both ended to satisfactory results; however, PSO relatively outperformed GA in terms of solution optimality and computational time.

Automated summary

The crew scheduling problem was solved using a single model that combined crew pairing and crew rostering problems, allowing crew members to have one or more days off. Genetic Algorithm and Particle Swarm Optimization were utilized to solve the model, with PSO showing superior performance in solution optimality and computational time.