Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching
Computational Optimization and Applications
Best Practice Simulated Annealing for the Airline Crew Scheduling Problem
Journal of Heuristics
An Approximate Model and Solution Approach for the Long-Haul Crew Pairing Problem
Transportation Science
The Operational Airline Crew Scheduling Problem
Transportation Science
Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling
Transportation Science
Efficient trip generation with a rule modeling system for crew scheduling problems
Journal of Systems and Software
Improving Crew Scheduling by Incorporating Key Maintenance Routing Decisions
Operations Research
Computers and Operations Research
Solving a large-scaled crew pairing problem by using a genetic algorithm
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
A constructive hybrid algorithm for crew pairing optimization
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
Computational results with a primal-dual subproblem simplex method
Operations Research Letters
Hi-index | 0.00 |
This paper presents a multiobjective genetic algorithm (MOGA)to solve the train crew pairing problem in railway companies. The proposed MOGA has several features, such as 1) A permutation-based model is proposed rather than the 0-1 set partition model. 2) Instead of pre-assigning a fixed group number of crewmembers, the proposed method can determine it by performing the evolutionary process. 3) The crossover and mutation operators are enhanced so that the duty time and the duty period can be integrated and considered during the evolutionary process. Experiments show that the proposed MOGA can find out optimal solution with exact group number of crewmembers instead of pre-assigning it so that the effective and efficient crew pairing can be yielded.