Title :
Modeling and Solving for Railway Crew Scheduling Problem
Author :
Wang, Fuzhang ; Wang, Haixing ; Shen, Jinsheng
Author_Institution :
Inst. of Comput. Technol., China Acad. of Railway Sci., Beijing
Abstract :
An improved railway crew scheduling model was presented, and the objective was to schedule crews in such a way that the deadheading was minimized while the operational constraints were satisfied. Ant colony algorithm (ACA) was devised to solve railway crew scheduling problem (RCSP) based on principle of ACA used to solve vehicle routing problem (VRP). Improvement on route construction rule and pheromone updating rule was adopted on the basis of former algorithm. An example was analyzed to demonstrate the correctness of the application of this algorithm. It is proved that ACA is efficient and robust in solving RCSP
Keywords :
artificial life; minimisation; personnel; railways; scheduling; ant colony algorithm; deadheading minimization; intelligent transport systems; operational constraints; pheromone updating rule; railway crew scheduling problem; route construction rule; Algorithm design and analysis; Computers; Electronic mail; Processor scheduling; Rail transportation; Robustness; Routing; Scheduling algorithm; Traffic control; Vehicles; ant colony algorithm (ACA); intelligent transport systems (ITS); railway crew scheduling problem (RCSP); vehicle routing problem (VRP;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713663
