چكيده به لاتين
This thesis seeks to optimize train crew scheduling problem under uncertainty, crew scheduling problem consists two phases: crew pairing and crew rostering. This thesis, concentrates on crew pairing problem, in the first step, the research focus on minimizing the total costs of crew missions, and in the next step has tried to robust the solution by considering uncertainty in two parameters: “driving time” and “diving cost”.
First, the research explained network and graph theory. Then crew pairing mathematical model is presented. What is notable is, a crew mission will start from a train crew depot and will finish at the same depot after a number of trips. So each depot has its own missions, and each trip must be covered by these missions at least once.
In the next step, Two-Stage Stochastic programming model for the crew pairing problem, is suggested by considering: “driving time” and “diving cost” as uncertain parameters. Also the sample was selected from Islamic Republic of Iran Railways and the result are shown.
The results show that, crew pairing total costs has reduced due to reduction in the extra rest time of crews.
