2019
DOI: 10.3390/su11133701
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Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model

Abstract: At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sections, resulting in a waste of capacity. In view of this situation, this paper develops a nonlinear integer programming model to determine an optimal timetable with a balanced scheduling mode, where the wasted capac… Show more

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Cited by 12 publications
(4 citation statements)
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References 31 publications
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“…The optimization theory is also used in addressing the power optimization issues of the communication systems to fulfill the different demands of different message types regarding the QoS, length of packet and transmission rates ?. The optimization theory has also been used to increase the efficiency of the urban rail timetable (Xue et al, 2019). The authors propose a nonlinear integer program in order to obtain a rail timetable which is efficient.…”
Section: Related Workmentioning
confidence: 99%
“…The optimization theory is also used in addressing the power optimization issues of the communication systems to fulfill the different demands of different message types regarding the QoS, length of packet and transmission rates ?. The optimization theory has also been used to increase the efficiency of the urban rail timetable (Xue et al, 2019). The authors propose a nonlinear integer program in order to obtain a rail timetable which is efficient.…”
Section: Related Workmentioning
confidence: 99%
“…Optimization of timetables with regard on vehicle capacity utilization is highlighted by Xue et al (2019).…”
Section: State Of the Artmentioning
confidence: 99%
“…Grey water footprint caused by crop production should be no more than the current footprints prior to optimization to avoid the overly serious impact of the optimized results on the environment. The constraints are represented by Equation (9).…”
Section: Grey Water Footprint Constraintsmentioning
confidence: 99%
“…Previously, programming models have been widely used to address optimization problems in many fields [7][8][9][10][11]. There also were many attempts in agricultural systems which used optimization methods [12,13].…”
Section: Introductionmentioning
confidence: 99%