Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimi...Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.展开更多
This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and ...This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.展开更多
Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for interc...Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for intercity travel,it becomes imperative for metro agen-cies to optimize holiday timetables.This paper focuses on designing holiday timetables of the first service period for the metro network that connects to an IR station,aiming to enhance multimodal collaboration with IR timetables while ensuring seamless coordina-tion among various metro lines at the network level.A bi-objective model is proposed to maximize the temporal availability of metro network and minimize transfer waiting times for IR passengers traveling in early morning.To solve the model,an improved artificial bee colony algorithm(ABC)is designed,incorporating adaptive neighbour search and simu-lated annealing techniques.The effectiveness of the model and algorithm is verified using the Shanghai metro network and Hongqiao Railway Station.Results indicate a 9.46%increase in the temporal availability of metro network for IR passengers,coupled with a 9.68%reduction in passenger transfer waiting times.Notably,the study reveals that solely advancing operations of the IR-connected metro lines is inefficient.Instead,optimizing train timetables for the entire metro network proves to be a cost-effective approach to enhancing the overall service level of early-morning operations.Furthermore,the study emphasizes the significance of even-numbered train headways in reducing passenger transfer waiting times.展开更多
The energy consumption of a teaching building can be effectively reduced by timetable optimization.However,in most studies that explore methods to reduce building energy consumption by course timetable optimization,se...The energy consumption of a teaching building can be effectively reduced by timetable optimization.However,in most studies that explore methods to reduce building energy consumption by course timetable optimization,self-study activities are not considered.In this study,an MATLAB-EnergyPlus joint simulation model was constructed based on the Building Controls Virtual Test Bed platform to reduce building energy consumption by optimizing the course schedule and opening strategy of self-study rooms in a holistic way.The following results were obtained by taking a university in Xi’an as an example:(1)The energy saving percentages obtained by timetabling optimization during the heating season examination week,heating season non-examination week,cooling season examination week,and cooling season non-examination week are 35%,29.4%,13.4%,and 13.4%,respectively.(2)Regarding the temporal arrangement,most courses are scheduled in the morning during the cooling season and afternoon during the heating season.Regarding the spatial arrangement,most courses are arranged in the central section of the middle floors of the building.(3)During the heating season,the additional building energy consumption incurred by the opening of self-study rooms decreases when duty heating temperature increases.展开更多
基金supported by Talents Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities (Grant No.2021RC228)Special Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities (Grant No.2021YJS103).
文摘Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.
基金sponsored in part by the National Natural Science Foundation of China(No.71101109)the Open Fund of the Key Laboratory of Highway Engineering of Ministry of Education,Changsha University of Science & Technology(No.kfj120108)
文摘This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.
基金funded by the Natural Science Foundation of Zhejiang Province(No.LY21E080008)the Natural Science Foundation of Ningbo(No.202003N4146)the National Natural Science Foundation of China(No.51408323).
文摘Metro plays a vital role in managing passenger distribution at intercity railway(IR)sta-tions,particularly during holidays when there is a surge in tourist traffic.To efficiently accommodate the high demand for intercity travel,it becomes imperative for metro agen-cies to optimize holiday timetables.This paper focuses on designing holiday timetables of the first service period for the metro network that connects to an IR station,aiming to enhance multimodal collaboration with IR timetables while ensuring seamless coordina-tion among various metro lines at the network level.A bi-objective model is proposed to maximize the temporal availability of metro network and minimize transfer waiting times for IR passengers traveling in early morning.To solve the model,an improved artificial bee colony algorithm(ABC)is designed,incorporating adaptive neighbour search and simu-lated annealing techniques.The effectiveness of the model and algorithm is verified using the Shanghai metro network and Hongqiao Railway Station.Results indicate a 9.46%increase in the temporal availability of metro network for IR passengers,coupled with a 9.68%reduction in passenger transfer waiting times.Notably,the study reveals that solely advancing operations of the IR-connected metro lines is inefficient.Instead,optimizing train timetables for the entire metro network proves to be a cost-effective approach to enhancing the overall service level of early-morning operations.Furthermore,the study emphasizes the significance of even-numbered train headways in reducing passenger transfer waiting times.
基金supported by the National Natural Science Foundation of China (52008328)National Key Research and Development Project (2018YFD1100202)+1 种基金the Science and Technology Department of Shaanxi Province (2020SF-393,2018ZDCXL-SF-03-04)the State Key Laboratory of Green Building in Western China (LSZZ202009).
文摘The energy consumption of a teaching building can be effectively reduced by timetable optimization.However,in most studies that explore methods to reduce building energy consumption by course timetable optimization,self-study activities are not considered.In this study,an MATLAB-EnergyPlus joint simulation model was constructed based on the Building Controls Virtual Test Bed platform to reduce building energy consumption by optimizing the course schedule and opening strategy of self-study rooms in a holistic way.The following results were obtained by taking a university in Xi’an as an example:(1)The energy saving percentages obtained by timetabling optimization during the heating season examination week,heating season non-examination week,cooling season examination week,and cooling season non-examination week are 35%,29.4%,13.4%,and 13.4%,respectively.(2)Regarding the temporal arrangement,most courses are scheduled in the morning during the cooling season and afternoon during the heating season.Regarding the spatial arrangement,most courses are arranged in the central section of the middle floors of the building.(3)During the heating season,the additional building energy consumption incurred by the opening of self-study rooms decreases when duty heating temperature increases.
