دانلود رایگان مقاله انگلیسی همگام سازی جدول زمانی حمل و نقل عمومی و برنامه ریزی خودرو با مطالبه قانونی - الزویر 2017

عنوان فارسی
همگام سازی جدول زمانی حمل و نقل عمومی یکپارچه و برنامه ریزی خودرو با مطالبه قانونی: مدل Bi-objective و Bi-level با استفاده از رویکرد کمبود عملکرد
عنوان انگلیسی
Integrated Public Transport Timetable Synchronization and Vehicle Scheduling with Demand Assignment: A Bi-objective Bi-level Model Using Deficit Function Approach
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
21
سال انتشار
2017
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E8693
رشته های مرتبط با این مقاله
مهندسی عمران
گرایش های مرتبط با این مقاله
مهندسی راه و ترابری، برنامه ریزی حمل و نقل
مجله
تحقیقات حمل و نقل بخش ب - Transportation Research Part B
دانشگاه
Department of Civil and Environmental Engineering - The University of Auckland - New Zealand
کلمات کلیدی
حمل و نقل عمومی، هماهنگ سازی جدول زمانی، زمانبندی خودرو، تخصیص تقاضا، مدل دو بعدی دو جانبه، تابع عمل
چکیده

abstract


In the operations planning process of public transport (PT), timetable synchronization is a useful strategy utilized to reduce transfer waiting time and improve service connectivity. However, most of the studies on PT timetable synchronization design have treated the problem independently of other operations planning activities, and have focused only on minimizing transfer waiting time. In addition, the impact of schedule changes on PT users’ route/trip choice behavior has not been well investigated yet. This work develops a new bi-objective, bi-level integer programming model, taking into account the interests of PT users and operators in attaining optimization of PT timetable synchronization integrated with vehicle scheduling and considering user demand assignment. Based on the special structure characteristics of the model, a novel deficit function (DF)-based sequential search method combined with network flow and shifting vehicle departure time techniques is proposed to achieve a set of Pareto-efficient solutions. The graphical features of the DF can facilitate a decision-making process for PT schedulers for finding a desirable solution. Two numerical examples are illustrated to demonstrate the methodology developed.

نتیجه گیری

6. Conclusions and further studies


The development of synchronized timetables for providing more user-oriented, system-optimal and well-connected public transport (PT) service is attracting ever-increasing attention. However, most previous studies on the PT timetable synchronization design problem are focused on maximizing the number of simultaneous arrivals (or arrivals within a time window) of vehicles at transfer stops, or on minimizing the total passenger transfer waiting time. Other operations activities and system performance measures are not explicitly taken into consideration, and nor has the impact of schedule changes on PT users’ route/trip choice behavior been well investigated. To bridge these gaps, this study provides a new multi-criteria optimization modelling framework using a systems approach for the integrated PT timetable synchronization and vehicle scheduling problem with passenger demand assignment. A new bi-objective, bi-level mathematical programming model that takes into account both PT user and operator interests is proposed. The nature of the overall mathematical formulations of the new model is bi-objective, bi-level integer programming, which is non-linear and non-convex. Based on the special structural characteristics of the model, a novel deficit function (DF)-based sequential search method, which is combined with a network-flow technique and a shifting departure time (route offset time) procedure, is proposed to solve the problem to obtain a set of Pareto-efficient solutions. The graphical features of the DF and the two-dimensional fleet-cost space can facilitate the decision-making process of PT schedulers in finding a desirable solution. Numerical results from a small PT network and a case study of the Spiess–Florian network demonstrate that the proposed model and solution method are effective and have potential for being applied to large scale and realistic networks.


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