Integer and combinatorial optimization
Integer and combinatorial optimization
A global approach to crew-pairing optimization
IBM Systems Journal
Management Science
Introduction to Algorithms
Parallel Algorithms for Airline Crew Planning on Networks of Workstations
ICPP '98 Proceedings of the 1998 International Conference on Parallel Processing
Parallel Crew Scheduling in PAROS
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on Parallel Processing
Modeling and Solving the Crew Rostering Problem
Operations Research
A Heuristic Method for the Set Covering Problem
Operations Research
Transportation Science
Airline Crew Scheduling with Regularity
Transportation Science
PSO-based algorithm for home care worker scheduling in the UK
Computers and Industrial Engineering
Multiobjective genetic algorithm to solve the train crew scheduling problem
ISTASC'10 Proceedings of the 10th WSEAS international conference on Systems theory and scientific computation
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Trip generation is the most time consuming phase in the solution process of crew scheduling problems faced by large transportation companies such as airlines and railways. A large number of trips must be constructed while satisfying a complex set of regulations. In this paper, we present an efficient trip generation method that utilizes originally a rule modeling system in order to reduce the corresponding search space. Special pruning rules are defined using a high-level rule language, which also supports the modeling of the business regulations required in the scheduling process. In addition, the legality checking mechanism involved has been tuned to perform efficiently in order to cope with the vast amount of the legality checks required by the trip generator. The algorithms are tested as a module for a crew scheduling application satisfying the tight response time requirements of a production system. We present experimental results based on problems provided by a major European airline that validate the usefulness and applicability of our work.