Solving the Master Linear Program in Column Generation Algorithms for Airline Crew Scheduling using a Subgradient Method

Cockpit Crew Pairing Problem in Airline Scheduling: Shortest Path with Resources Constraints Approach

Increasing competition in the air transport market has intensified active airlines’ efforts to keep their market share by attaching due importance to cost management aimed at reduced final prices. Crew costs are second only to fuel costs on the cost list of airline companies. So, this paper attempts to investigate the cockpit crew pairing problem. The set partitioning problem has been used for ...

An Effective Deflected Subgradient Optimization Scheme for Implementing Column Generation for Large-Scale Airline Crew Scheduling Problems

A Heuristic Approach to Column Generation for Airline Crew Scheduling

Airline crew scheduling gives rise to many diicult and interesting optimisation problems. With straightforward approaches to the crew pairing problem one speciically needs to solve very large set-covering problems. One suggested approach to these problems is column generation. In column generation, the choice of master solver can have a signiicant impact on performance, both with respect to spe...

Improvement of Column Generation Method for Railway Crew Scheduling Problems

The railway crew scheduling problem is to determine an optimal crew assignment to minimize the number of crews required to cover all of railway assignment satisfying several crew working constraints. The problem can be formulated as a huge set covering problem. Column generation method is commonly used to solve the railway crew scheduling problem. Conventional column generation method has a sho...

Dynamic Aggregation of Set-Partitioning Constraints in Column Generation

Column generation is often used to solve problems involving set-partitioning constraints, such as vehicle-routing and crew-scheduling problems. When these constraints are in large numbers and the columns have on average more than 8–12 nonzero elements, column generation often becomes inefficient because solving the master problem requires very long solution times at each iteration due to high d...