The role of cross-border commuting needs is remarkable, given that large cross-border cities tend to have high traffic attractiveness. Thus, agglomeration effects are strongly prevalent in populous settlements close to the border. This is due to the fact that both Hungary and the neighboring countries are burdened by spatial inequalities; therefore, the traffic at the individual border crossing points is unbalanced. Our aim is to show the extent to which the introduction of certain public transport modes contributes to the reduction of cross-border passenger car traffic. In order to do this, we have to set up a spatial econometric model that can simultaneously handle the parallel public transport infrastructure, the cross-border attractiveness of border cities, and the impact of spatial inequalities. The results of the research shed light on how the introduction of each means of transport contributes to increasing the competitiveness of border regions. This will demonstrate the effectiveness of policy tools that can improve the competitiveness of a given macroregion.
{"title":"Spatial Econometric Cross-Border Traffic Analysis for Passenger Cars – Hungarian Experience","authors":"T. Sipos, Z. Szabó, Á. Török","doi":"10.7307/PTT.V33I2.3641","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3641","url":null,"abstract":"The role of cross-border commuting needs is remarkable, given that large cross-border cities tend to have high traffic attractiveness. Thus, agglomeration effects are strongly prevalent in populous settlements close to the border. This is due to the fact that both Hungary and the neighboring countries are burdened by spatial inequalities; therefore, the traffic at the individual border crossing points is unbalanced. Our aim is to show the extent to which the introduction of certain public transport modes contributes to the reduction of cross-border passenger car traffic. In order to do this, we have to set up a spatial econometric model that can simultaneously handle the parallel public transport infrastructure, the cross-border attractiveness of border cities, and the impact of spatial inequalities. The results of the research shed light on how the introduction of each means of transport contributes to increasing the competitiveness of border regions. This will demonstrate the effectiveness of policy tools that can improve the competitiveness of a given macroregion.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84967027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.
{"title":"Hierarchical Passenger Hub Location Problem in a Megaregion Area Considering Service Availability","authors":"Huang Yan, Xiaoning Zhang, Xiao-lin Wang","doi":"10.7307/PTT.V33I2.3563","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3563","url":null,"abstract":"The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81411272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Improving safety has always been the top interest in the aviation industry. The outcomes of safety and risk analyses have become much more thorough and sophisticated. They have become an industry standard of safety investigations in many airlines nowadays. In the past, airlines were much more limited in answering the questions about hazardous situations, accident probabilities, and accident rates. Airlines try hard to cope with stricter safety standards. The objective of this paper is to find out and quantify the extent of the expert judgment in helping airlines in the evaluation of the Flight Data Monitoring (FDM) events. On top of that, the paper reveals the method for a careful choice of experts, so that their estimations will maximize the potential of an accurate and useful outcome. Also, the paper provides details of implementation of the classical model into this research, then continues with the calculations and visualization of the outcomes. The outcomes are probability distributions per each aircraft type, then per IATA accident type and finally per FDM event.
{"title":"The Use of Expert Judgement Methods for Deriving Accident Probabilities in Aviation","authors":"Benedikt Badánik, M. Jánossy, A. Dijkstra","doi":"10.7307/PTT.V33I2.3634","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3634","url":null,"abstract":"Improving safety has always been the top interest in the aviation industry. The outcomes of safety and risk analyses have become much more thorough and sophisticated. They have become an industry standard of safety investigations in many airlines nowadays. In the past, airlines were much more limited in answering the questions about hazardous situations, accident probabilities, and accident rates. Airlines try hard to cope with stricter safety standards. The objective of this paper is to find out and quantify the extent of the expert judgment in helping airlines in the evaluation of the Flight Data Monitoring (FDM) events. On top of that, the paper reveals the method for a careful choice of experts, so that their estimations will maximize the potential of an accurate and useful outcome. Also, the paper provides details of implementation of the classical model into this research, then continues with the calculations and visualization of the outcomes. The outcomes are probability distributions per each aircraft type, then per IATA accident type and finally per FDM event.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73765844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Huang, Yimin Wang, Peiqun Lin, Heng Yu, Yue Luo
Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and simultaneously help traffic operators develop a passenger organization strategy. However, short-term passenger flow prediction needs to consider many factors, and the results of the existing models for short-term subway passenger flow forecasting are often unsatisfactory. Along this line, we propose a parallel architecture, called the seasonal and nonlinear least squares support vector machine (SN-LSSVM), to extract the periodicity and nonlinearity characteristics of passenger flow. Various forecasting models, including auto-regressive integrated moving average, long short-term memory network, and support vector machine, are employed for evaluating the performance of the proposed architecture. Moreover, we first applied the method to the Tiyu Xilu station which is the most crowded station in the Guangzhou metro. The results indicate that the proposed model can effectively make all-weather and year-round passenger flow predictions, thus contributing to the management of the station.
{"title":"Forecasting the All-Weather Short-Term Metro Passenger Flow Based on Seasonal and Nonlinear LSSVM","authors":"Xin Huang, Yimin Wang, Peiqun Lin, Heng Yu, Yue Luo","doi":"10.7307/PTT.V33I2.3561","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3561","url":null,"abstract":"Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and simultaneously help traffic operators develop a passenger organization strategy. However, short-term passenger flow prediction needs to consider many factors, and the results of the existing models for short-term subway passenger flow forecasting are often unsatisfactory. Along this line, we propose a parallel architecture, called the seasonal and nonlinear least squares support vector machine (SN-LSSVM), to extract the periodicity and nonlinearity characteristics of passenger flow. Various forecasting models, including auto-regressive integrated moving average, long short-term memory network, and support vector machine, are employed for evaluating the performance of the proposed architecture. Moreover, we first applied the method to the Tiyu Xilu station which is the most crowded station in the Guangzhou metro. The results indicate that the proposed model can effectively make all-weather and year-round passenger flow predictions, thus contributing to the management of the station.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73947326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
COVID-19 caused by the SARS-CoV-2 virus is a global health concern due to the quick spread of the disease In Turkey, the first confirmed COVID-19 case and death occurred on 11 and 15 March 2020, respectively There is a lack of research on the impact of COVID-19 on public transportation mobility and the Air Quality Index (AQI) around the world The objective of this research is to consider the impact of COVID-19 on public transportation usage and consequently the AQI level in Turkey Data collection for the analysis of public transportation usage and the air quality status during pre-lockdown and lockdown was carried out using the public transportation applications Moovit and World's Air Pollution The results demonstrated that during the lockdown in Ankara and Istanbul, public transportation usage dramatically decreased by more than 80% by the end of March and did not change significantly until the end of May As regards air quality, the results confirmed that air quality improved significantly during the lockdown For Ankara and Istanbul, the improvement was estimated at about 9% and 47%, respectively
{"title":"Impact of Covid-19 on Public Transportation Usage and Ambient Air Quality in Turkey","authors":"M. Sahraei, Emre Kuşkapan, M. Çodur","doi":"10.7307/PTT.V33I2.3704","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3704","url":null,"abstract":"COVID-19 caused by the SARS-CoV-2 virus is a global health concern due to the quick spread of the disease In Turkey, the first confirmed COVID-19 case and death occurred on 11 and 15 March 2020, respectively There is a lack of research on the impact of COVID-19 on public transportation mobility and the Air Quality Index (AQI) around the world The objective of this research is to consider the impact of COVID-19 on public transportation usage and consequently the AQI level in Turkey Data collection for the analysis of public transportation usage and the air quality status during pre-lockdown and lockdown was carried out using the public transportation applications Moovit and World's Air Pollution The results demonstrated that during the lockdown in Ankara and Istanbul, public transportation usage dramatically decreased by more than 80% by the end of March and did not change significantly until the end of May As regards air quality, the results confirmed that air quality improved significantly during the lockdown For Ankara and Istanbul, the improvement was estimated at about 9% and 47%, respectively","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74268347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Livia Maglić, Tomislav Krljan, N. Grubišić, Lovro Maglić
The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.
{"title":"Estimating Urban Road Transport Vehicles Emissions in the Rijeka City Streets","authors":"Livia Maglić, Tomislav Krljan, N. Grubišić, Lovro Maglić","doi":"10.7307/PTT.V33I2.3613","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3613","url":null,"abstract":"The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80582028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coach emergency escape research is an effective measure to reduce casualties under serious vehicle fire accidents. A novel experiment method employing a wireless transducer was implemented and the head rotation speed, rotation moment and rotation duration were collected as the input variables for the classification and regression tree (CART) model. Based on this model, the classification result explicitly pointed out that the exit searching efficiency was evolving. By ignoring the last three unimportant factors from the Analytic Hierarchy Process (AHP), the ultimate Dynamic Bayesian Network (DBN) was built with the temporal part of the CART output and the time-independent part of the vehicle characteristics. Simulation showed that the most efficient exit searching period is the middle escape stage, which is 10 seconds after the emergency signal is triggered, and the escape probability clearly increases with the efficient exit searching. Furthermore, receiving emergency escape training contributes to a significant escape probability improvement of more than 10%. Compared with different failure modes, the emergency hammer layout and door reliability have a more significant influence on the escape probability improvement than aisle condition. Based on the simulation results, the escape probability will significantly drop below 0.55 if the emergency hammers, door, and aisle are all in a failure state.
{"title":"Dynamic Bayesian Network-Based Escape Probability Estimation for Coach Fire Accidents","authors":"Chenyu Zhou, Xuan Zhao, Qiang Yu, Rong Huang","doi":"10.7307/PTT.V33I2.3537","DOIUrl":"https://doi.org/10.7307/PTT.V33I2.3537","url":null,"abstract":"Coach emergency escape research is an effective measure to reduce casualties under serious vehicle fire accidents. A novel experiment method employing a wireless transducer was implemented and the head rotation speed, rotation moment and rotation duration were collected as the input variables for the classification and regression tree (CART) model. Based on this model, the classification result explicitly pointed out that the exit searching efficiency was evolving. By ignoring the last three unimportant factors from the Analytic Hierarchy Process (AHP), the ultimate Dynamic Bayesian Network (DBN) was built with the temporal part of the CART output and the time-independent part of the vehicle characteristics. Simulation showed that the most efficient exit searching period is the middle escape stage, which is 10 seconds after the emergency signal is triggered, and the escape probability clearly increases with the efficient exit searching. Furthermore, receiving emergency escape training contributes to a significant escape probability improvement of more than 10%. Compared with different failure modes, the emergency hammer layout and door reliability have a more significant influence on the escape probability improvement than aisle condition. Based on the simulation results, the escape probability will significantly drop below 0.55 if the emergency hammers, door, and aisle are all in a failure state.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79467238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Signal Phase and Timing (SPaT) message is an important input for research and applications of Connected Vehicles (CVs). However, the actuated signal controllers are not able to directly give the SPaT information since the SPaT is influenced by both signal control logic and real-time traffic demand. This study elaborates an estimation method which is proposed according to the idea that an actuated signal controller would provide similar signal timing for similar traffic states. Thus, the quantitative description of traffic states is important. The traffic flow at each approaching lane has been compared to fluids. The state of fluids can be indicated by state parameters, e.g. speed or height, and its energy, which includes kinetic energy and potential energy. Similar to the fluids, this paper has proposed an energy model for traffic flow, and it has also added the queue length as an additional state parameter. Based on that, the traffic state of intersections can be descripted. Then, a pattern recognition algorithm was developed to identify the most similar historical states and also their corresponding SPaTs, whose average is the estimated SPaT of this second. The result shows that the average error is 3.1 seconds.
{"title":"Estimating Signal Timing of Actuated Signal Control Using Pattern Recognition under Connected Vehicle Environment","authors":"Ruochen Hao, Ling Wang, Wanjing Ma, Chunhui Yu","doi":"10.7307/PTT.V33I1.3555","DOIUrl":"https://doi.org/10.7307/PTT.V33I1.3555","url":null,"abstract":"The Signal Phase and Timing (SPaT) message is an important input for research and applications of Connected Vehicles (CVs). However, the actuated signal controllers are not able to directly give the SPaT information since the SPaT is influenced by both signal control logic and real-time traffic demand. This study elaborates an estimation method which is proposed according to the idea that an actuated signal controller would provide similar signal timing for similar traffic states. Thus, the quantitative description of traffic states is important. The traffic flow at each approaching lane has been compared to fluids. The state of fluids can be indicated by state parameters, e.g. speed or height, and its energy, which includes kinetic energy and potential energy. Similar to the fluids, this paper has proposed an energy model for traffic flow, and it has also added the queue length as an additional state parameter. Based on that, the traffic state of intersections can be descripted. Then, a pattern recognition algorithm was developed to identify the most similar historical states and also their corresponding SPaTs, whose average is the estimated SPaT of this second. The result shows that the average error is 3.1 seconds.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87289973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In times of ever stronger awareness of environmental protection and potentiation of a beneficial modal split, the railway sector with efficient asset utilization and proper investment planning has the highest chance of meeting customer expectations and attracting new users more effectively. Continuous increase in railway demand leads to an increase in the utilization of railway infrastructure, and the inevitable lack of capacity, a burning problem that many national railways are continually facing. To address it more effectively, this paper reviews available methodologies for railway capacity determination and techniques for its enhancement in the recent scientific literature. Particular focus is given to the possibility of increasing railway capacity through signalling systems and installing the European Train Control System (ETCS). The most important relationships with segments of existing research have been identified, and in line with this, the directions for a potential continuation of research are suggested.
{"title":"Railway Capacity Enhancement with Modern Signalling Systems – A Literature Review","authors":"Matea Mikulčić, T. Mlinarić","doi":"10.7307/PTT.V33I1.3664","DOIUrl":"https://doi.org/10.7307/PTT.V33I1.3664","url":null,"abstract":"In times of ever stronger awareness of environmental protection and potentiation of a beneficial modal split, the railway sector with efficient asset utilization and proper investment planning has the highest chance of meeting customer expectations and attracting new users more effectively. Continuous increase in railway demand leads to an increase in the utilization of railway infrastructure, and the inevitable lack of capacity, a burning problem that many national railways are continually facing. To address it more effectively, this paper reviews available methodologies for railway capacity determination and techniques for its enhancement in the recent scientific literature. Particular focus is given to the possibility of increasing railway capacity through signalling systems and installing the European Train Control System (ETCS). The most important relationships with segments of existing research have been identified, and in line with this, the directions for a potential continuation of research are suggested.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80693070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper deals with robust optimization and network flows. Several robust variants of integer flow problems are considered. They assume uncertainty of network arc capacities as well as of arc unit costs (where applicable). Uncertainty is expressed by discrete scenarios. Since the considered variants of the maximum flow problem are easy to solve, the paper is mostly concerned with NP-hard variants of the minimum-cost flow problem, thus proposing an approximate algorithm for their solution. The accuracy of the proposed algorithm is verified by experiments.
{"title":"Solving Robust Variants of Integer Flow Problems with Uncertain Arc Capacities","authors":"Marko Spoljarec, R. Manger","doi":"10.7307/PTT.V33I1.3538","DOIUrl":"https://doi.org/10.7307/PTT.V33I1.3538","url":null,"abstract":"This paper deals with robust optimization and network flows. Several robust variants of integer flow problems are considered. They assume uncertainty of network arc capacities as well as of arc unit costs (where applicable). Uncertainty is expressed by discrete scenarios. Since the considered variants of the maximum flow problem are easy to solve, the paper is mostly concerned with NP-hard variants of the minimum-cost flow problem, thus proposing an approximate algorithm for their solution. The accuracy of the proposed algorithm is verified by experiments.","PeriodicalId":54546,"journal":{"name":"Promet-Traffic & Transportation","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84637045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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