Linear Bus Holding Model for Real Time Traffic Network Control. Hernández-Landa, L. G., Morales-Marroquín, M. L., Nigenda, R. S., & Ríos-Solís, Y. Á. Mota, M. M., la Mota, I.<nbsp>F.<nbsp>D., & Serrano, D. G., editors. Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice. Springer, 2014. To appear August 2015![Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex One of the most annoying problems in urban bus operations is bus bunching, which happens when two or more buses arrive at a stop nose to tail. Bus bunching reflects an unreliable service that affects transit operations by increasing passenger-waiting times. This work proposes a linear mathematical programming model that establishes bus holding times at certain stops along a transit corridor to avoid bus bunching. Our approach needs real-time input, so we simulate a transit corridor and apply our mathematical model to the data generated. Thus, the inherent variability of a transit system is considered by the simulation, while the optimization model takes into account the key variables and constraints of the bus operation. Our methodology reduces overall passenger-waiting times efficiently given our linear programming model, with the characteristic of applying control intervals just every 5 minutes.
@inbook{ landamoralessanchezrios2014,
author = {Leonardo G. Hernández-Landa and Miguel L. Morales-Marroquín and Romeo Sánchez Nigenda and Yasmín Á. Ríos-Solís},
chapter = {Linear Bus Holding Model for Real Time Traffic Network Control},
title = {Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice},
publisher = {Springer},
year = {2014},
editor = {Miguel Mujica Mota and Idalia Flores De la Mota and Daniel Guimarans Serrano},
isbn = {978-3-319-15032-1},
url = {http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-3-319-15032-1},
abstract = {One of the most annoying problems in urban bus operations is bus bunching, which happens when two or more buses arrive at a stop nose to tail. Bus bunching reflects an unreliable service that affects transit operations by increasing passenger-waiting times. This work proposes a linear mathematical programming model that establishes bus holding times at certain stops along a transit corridor to avoid bus bunching. Our approach needs real-time input, so we simulate a transit corridor and apply our mathematical model to the data generated. Thus, the inherent variability of a transit system is considered by
the simulation, while the optimization model takes into account the key variables
and constraints of the bus operation. Our methodology reduces overall passenger-waiting times efficiently given our linear programming model, with the characteristic of applying control intervals just every 5 minutes.},
note = {To appear August 2015},
keywords = {pisis, bus bunching, linear programming, simulation}
}
Downloads: 0
{"_id":"bmfpMfkFKiYjfKMTc","authorIDs":[],"author_short":["Hernández-Landa, L.<nbsp>G.","Morales-Marroquín, M.<nbsp>L.","Nigenda, R.<nbsp>S.","Ríos-Solís, Y.<nbsp>Á."],"bibbaseid":"hernndezlanda-moralesmarroqun-nigenda-rossols-appliedsimulationandoptimizationinlogisticsandindustrialandaeronauticalpractice-2014","bibdata":{"abstract":"One of the most annoying problems in urban bus operations is bus bunching, which happens when two or more buses arrive at a stop nose to tail. Bus bunching reflects an unreliable service that affects transit operations by increasing passenger-waiting times. This work proposes a linear mathematical programming model that establishes bus holding times at certain stops along a transit corridor to avoid bus bunching. Our approach needs real-time input, so we simulate a transit corridor and apply our mathematical model to the data generated. Thus, the inherent variability of a transit system is considered by the simulation, while the optimization model takes into account the key variables and constraints of the bus operation. Our methodology reduces overall passenger-waiting times efficiently given our linear programming model, with the characteristic of applying control intervals just every 5 minutes.","author":["Hernández-Landa, Leonardo G.","Morales-Marroquín, Miguel L.","Nigenda, Romeo Sánchez","Ríos-Solís, Yasmín Á."],"author_short":["Hernández-Landa, L.<nbsp>G.","Morales-Marroquín, M.<nbsp>L.","Nigenda, R.<nbsp>S.","Ríos-Solís, Y.<nbsp>Á."],"bibtex":"@inbook{ landamoralessanchezrios2014,\n author = {Leonardo G. Hernández-Landa and Miguel L. Morales-Marroquín and Romeo Sánchez Nigenda and Yasmín Á. Ríos-Solís},\n chapter = {Linear Bus Holding Model for Real Time Traffic Network Control},\n title = {Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice},\n publisher = {Springer},\n year = {2014},\n editor = {Miguel Mujica Mota and Idalia Flores De la Mota and Daniel Guimarans Serrano},\n isbn = {978-3-319-15032-1},\n url = {http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-3-319-15032-1},\n abstract = {One of the most annoying problems in urban bus operations is bus bunching, which happens when two or more buses arrive at a stop nose to tail. Bus bunching reflects an unreliable service that affects transit operations by increasing passenger-waiting times. This work proposes a linear mathematical programming model that establishes bus holding times at certain stops along a transit corridor to avoid bus bunching. Our approach needs real-time input, so we simulate a transit corridor and apply our mathematical model to the data generated. Thus, the inherent variability of a transit system is considered by\nthe simulation, while the optimization model takes into account the key variables\nand constraints of the bus operation. Our methodology reduces overall passenger-waiting times efficiently given our linear programming model, with the characteristic of applying control intervals just every 5 minutes.},\n note = {To appear August 2015},\n keywords = {pisis, bus bunching, linear programming, simulation}\n}","bibtype":"inbook","chapter":"Linear Bus Holding Model for Real Time Traffic Network Control","editor":["Mota, Miguel Mujica","la Mota, Idalia Flores De","Serrano, Daniel Guimarans"],"editor_short":["Mota, M.<nbsp>M.","la<nbsp>Mota, I.<nbsp>F.<nbsp>D.","Serrano, D.<nbsp>G."],"id":"landamoralessanchezrios2014","isbn":"978-3-319-15032-1","key":"landamoralessanchezrios2014","keywords":"pisis, bus bunching, linear programming, simulation","note":"To appear August 2015","publisher":"Springer","title":"Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice","type":"inbook","url":"http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-3-319-15032-1","year":"2014","bibbaseid":"hernndezlanda-moralesmarroqun-nigenda-rossols-appliedsimulationandoptimizationinlogisticsandindustrialandaeronauticalpractice-2014","role":"author","urls":{"Paper":"http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-3-319-15032-1"},"keyword":["pisis","bus bunching","linear programming","simulation"],"downloads":0,"html":""},"bibtype":"inbook","biburl":"https://googledrive.com/host/0B92aE0wdpf7TNVhQblE5VkNMWjQ/pubs_romeo.bib","creationDate":"2015-02-16T15:34:45.765Z","downloads":0,"keywords":["pisis","bus bunching","linear programming","simulation"],"search_terms":["applied","simulation","optimization","logistics","industrial","aeronautical","practice","hernández-landa","morales-marroquín","nigenda","ríos-solís"],"title":"Applied Simulation and Optimization: In Logistics and Industrial, and Aeronautical Practice","year":2014,"dataSources":["DnHLi7cHe7HWa5C3o"]}