Linear-Quadratic-Gaussian Optimization of Urban Transportation Network with Application to Sofia Traffic Optimization

Balabanov, A S; Stoilov, Todor; Boneva, Yordanka

doi:10.1515/cait-2016-0041

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Research on urban transportation literature spreads on a large area. While some of the researchers discuss the passengers' behavior in urban transportation (Choi et al, 2013;Brette et al, 2014), some of them investigate the environmental effects (He et al, 2011;Cheng et al, 2015) and optimization of the transportation network systems (Pu and Ma, 2014;Balabanov et al, 2016). The paper of Van Oudheusden et al (1987) which is one of the earliest studies in literature applied set covering model to solve the practical problem of bus route network design.…”

Section: Introductionmentioning

confidence: 99%

Accessing Analysis of Passengers Covered by Payment Kiosks: A Case for the Gaziantep Public Transportation System

Özceylan

Özkan

2019

Black Sea Journal of Engineering and Science

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Recently, the use of public transport has become widespread with the increasing population. This brings with it many problems. Since the points of payment kiosks are not regularly distributed where the population is concentrated, the most important problem is accessing to these kiosks. The accessing analysis of passengers covered by payment kiosks in Gaziantep, Turkey is considered in this study. 177 different locations which have the densest population are considered as the demand points and 379 payment kiosks are considered as the source points. All spatial data are obtained using a geographic information system (GIS). The goal of this study is to maximize the rate of passengers (demand points) who try to access to the payment kiosks. To do so, two different location-allocation analysis which are set covering and p-median models were applied using mathematical modeling approach. As a result, the required number of kiosks and coverage distances were determined to satisfy all demand.

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