الفهرس Only 14 pages are availabe for public view
 |  | from | 95 |  |  |
| | | from | 95 | | |
Abstract
In urban rail transit (URT) systems, implementing a skip-stop strategy aims at minimizing the average passenger travel time; reducing energy consumption; and relieving in-vehicle congestion. This thesis contributes in building up a methodology for implementing the skip-stop strategy practically. A detailed description of the problem is first proposed. This description itemizes different scenarios, passenger trips categories, and key factors that should be considered in implementing this strategy. Following, a data set generator is proposed to develop a number of test problems. After that, two mathematical models are formulated. The first model is a pure integer quadratic programming Model with the objective of maximizing the number of direct trips at a given number of non-skipped stations. The second is a non-linear programming model that aims to minimize total travel time of passengers. A linearization is performed for both models to be solved as Integer-linear programming models. In addition, a new heuristic algorithm is proposed to be used with large scale problems. This algorithm is a hierarchy of three-stages, first the feasible solution space is to be defined, after that, a near-optimal solution is to be obtained through a smart process to be used as the initial solution, and finally a local search is conducted to find the optimal solution. The optimal arrangement of stations regarding number of direct trips is obtained. On the other hand, travel time optimality higher than 99% on average is accomplished. Finally, the effectiveness of the strategy in URT systems is interpreted through conducting design of experiments