A Time-Space Network-Based Optimization Method for Scheduling Depot Drivers

The driver scheduling problem at Chinese electric multiple-unit train depots becomes more and difficult in practice is studied very little research. This paper focuses on defining, modeling, solving the depot which can determine size schedule simultaneously. To solve this problem, we first construct a time-space network based formulate as minimum-cost multi-commodity flow problem. We then develop Lagrangian relaxation heuristic to where upper bound two-phase method consisting of greedy local search method. conduct computational study test effectiveness our heuristic. results also report significance ratio task depot.