چكيده به لاتين
Today, one of the main costs of travel companies is the cost of expedited services. Therefore, shipping companies are looking for an optimal way to dispatch the crew, as it can help lower costs and more regular and balanced travel plans. Therefore, in this thesis, a modeling of a railway crew scheduling problem and the provision of work shift for the crew is discussed. The modeling of this problem is done with consideration of the existing uncertainty, and in order to carry out a merit and optimal allocation, the parameters of good performance of the crew are considered in the model. The problem has two objective functions. The first objective is to minimize costs, which include the cost of the main and deadhead travels, the cost of deviations from standard work time, and the cost of deviations from standard relief time. The second objective is to maximize the allocation of crew to better paths. The constraints of this problem are the number of crew required per travel, the duration of the travel, the time between two consecutive travels (short rest), the rest time between two consecutive periods (long rest) and spatial sequence of consecutive travels. The GRASP method was used to solve this problem. A lexicographic method was used to solve the problem. In order to find feasible solutions for the first function, the GRASP method was used with a reactive threshold parameter. After using the GRASP method, the crew will be selected from the crew of the candidate based on the second objective function. The case study of this thesis is related to one of the passenger railway companies of Iran Railways. The company has 12 paths and about 160 crew members. This problem has been defuzzified by Jimenez method and solved using GRASP method. The results for center of gravity and Jimenez methods show a decrease of 7% and 8% of costs compared to the situation in the case study respectively. Also the upper and lower limits of the uncertain problem are 9% and 5% respectively, as compared to the current cost of the situation in the case study.
Keywords: Crew scheduling, Optimization, Scheduling, Rostering, Railway
