چكيده به لاتين
Abstract
The problem of timetabling and planning in recent decades is one of the most challenging issues of optimization. One of the most important issues of the day is the optimization of the timetable for transportation networks, including the city rail network. The purpose of this research is to provide a mathematical model for timing the movement of urban railroads at intersection stations.
First, a two-objective optimization model has been proposed. The first objective is to reduce the waiting time for passengers when moving at intersections, and the second is to reduce operating costs. Among the limitations of this model, calculation of the arrival and departure time of the train to/from the intersection stations, calculation of the headway, passenger waiting time and the number of required fleets, can be mentioned. To validate the model, Tehran metro network with 8 main lines and 6 intersection stations has been selected as case study. Then, two methods solving of "LP-metric" and the "Augmented epsilon constraint" have been used to solve a definite proposed model. The results of the analysis of these two solving methods show that Augmented epsilon constraint method has a higher efficiency in the production of pareto solutions as well as less solving time.
Also, in this research, a non-deterministic scenario-based model is proposed that the parameter of the number of passengers and the time of moving passengers is considered uncertain and the non-deterministic model is based on the "mulvey" method. Similar to the definitive model, Tehran metro network has been selected as a case study. The proposed bi-objective robust model is solved by the Augmented epsilon constraint method.
The results of the definitive and robust optimization model are examined individually and also compared with each other. Numerical results show that the model is robust versus uncertainty and indicate the efficiency and effectiveness of the uncertain model at logical solving time. Among the research limitations is the absence of a system for counting the number of passengers traveling at intersections.
Keywords: timetabling, urban train, intersection, uncertainty, robust optimization
