Browsing by Author "Sheu, JB"

Now showing 1 - 17 of 17

A composite traffic flow modeling approach for incident-responsive network traffic assignment
(2006-07-15)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents a hybrid traffic simulation-based model to address the network traffic route choice issue under conditions of lane-blocking incidents on surface streets. The proposed approach includes four sequential mechanisms: (1) link flow loading, (2) link traffic moving, (3) link cost calculation, and (4) searching the shortest path. To deal with the traffic flows moving on lane-blocking links, specific incident-induced link traffic flow models, which are extended from the Lighthill-Whitham (L-W for short) model, are formulated. A simulation-based approach is then proposed to determine the instantaneous shortest path associated with each vehicle approaching to each given intersection on the network. In addition, numerical examples associated with diverse incident scenarios are investigated. The numerical results demonstrate the competitiveness of the proposed simulation-based method by reducing the network-wide path travel time by 11.4% and the incident impact on link traffic flows by 66.7% in comparison with the Paramics traffic simulator. It is expected that this study can provide linkage between the fields of incident management and dynamic traffic assignment that will allow the development of such related technologies as real-time incident-responsive route guidance and incident management systems. (c) 2005 Elsevier B.V. All rights reserved.
A fuzzy-based customer classification method for demand-responsive logistical distribution operations
(2003-10-16)
Hu, TL
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Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
In some cases, customer classification is important for the development of advanced logistical distribution strategies in response to the growing complexity in business logistical markets. This paper presents a new approach that can be employed to cluster customers before executing fleet routing in logistical operations. The proposed approach is developed on the basis of fuzzy clustering techniques, and involves three sequential mechanisms including: (1) binary transformation, (2) generation of a fuzzy correlation matrix, and (3) customer clustering. Such a customer clustering method should be performed prior to vehicle dispatching and routing in the process of goods distribution. The proposed methodology clusters customers on the basis of their demand attributes, rather than the static geographic property which is considered extensively in most published vehicle routing algorithms. In addition to methodology development, a case study was conducted to demonstrate the potential advantages of the proposed fuzzy clustering based method. It is expected that this study can stimulate more research on time-based logistics control and management. (C) 2002 Elsevier B.V. All rights reserved.
A hybrid fuzzy-based approach for identifying global logistics strategies
(2004-01-01)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents a hybrid fuzzy-based method that integrates fuzzy-AHP and fuzzy-MADM approaches for identifying global logistics (GL) strategies when corresponding supply and demand environments are complicated and uncertain. Before applying the methodology, six typical types of GL strategic modes were specified with their distinctive channels of physical distribution and information flows. Survey data collected from integrated circuit (IC) manufacturers in Taiwan was used to demonstrate the applicability of the proposed method. The empirical results indicate that the proposed method can be used to identify GL strategies when the factors that influence GL are complex and uncertain. (C) 2003 Elsevier Ltd. All rights reserved.
A novel model for quick response to disaster relief distribution
(2005)
Sheu, JB
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Chen, YH
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Lan, LW
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents a hybrid fuzzy-optimization methodology to solve the large-scale disaster relief distribution problem with the main goal of minimizing the total number of fatalities. The proposed method mainly contains a three-stage operational algorithm. Here fuzzy clustering techniques are used in the first stage to classify the damaged areas based on respective relief demand attributes and priority, followed by the second and the third stage, where fuzzy linear programming is employed to deal with the situation when the demand for victims is greater than the available resources. Results of a numerical study are illustrated to demonstrate the applicability of the proposed method.
A reverse logistics cost minimization model for the treatment of hazardous wastes
(2002-11-01)
Hu, TL
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Sheu, JB
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Huang, KH
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study presents a cost-minimization model for a multi-time-step, multi-type hazardous-waste reverse logistics system. A discrete-time linear analytical model is formulated that minimizes total reverse logistics operating costs subject to constraints that take into account such internal and external factors as business operating strategies and governmental regulations. Application cases are presented to demonstrate the feasibility of the proposed approach. By using the proposed model coupled with operational strategies, it is shown that the total reverse logistics costs for the applications cases can be reduced by more than 49%. (C) 2002 Elsevier Science Ltd. All rights reserved.
A sequential detection approach to real-time freeway incident detection and characterization
(2004-09-01)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
In this paper, a new methodology is presented for real-time detection and characterization of freeway incidents. The proposed technology is capable of detecting freeway incidents in real time as well as characterizing incidents in terms of time-varying lane-changing fractions and queue lengths in blocked lanes, the lanes blocked due to incidents, and duration of incident, etc. The architecture of the proposed incident detection approach consists of three sequential procedures: (1) symptom identification for identification of anomalous changes in traffic characteristics probably caused by incidents, (2) signal processing for stochastic estimation of incident-related lane traffic characteristics, and (3) pattern recognition for incident detection. Lane traffic count and occupancy are two major types of input data, which can be readily collected from point detectors. The primary techniques utilized to develop the proposed method include: (1) discrete-time, nonlinear, stochastic system modeling used in the signal processing procedure, and (2) modified sequential probability ratio tests employed in the pattern recognition procedure. Off-line tests were conducted to substantiate the performance of the proposed incident detection algorithm based on simulated data generated employing the calibrated INTRAS simulation model and on real incident data collected on the I-880 freeway in Oakland, California. The test results indicate the feasibility of achieving real-time incident detection and characterization utilizing the proposed method. (C) 2003 Elsevier B.V. All rights reserved.
A stochastic modeling approach to real-time prediction of queue overflows
(2003-02-01)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Queue overflow is a critical issue in developing queue prediction technologies for applications in Advanced Transportation Management System (ATMS). Conventional queue prediction methods, however, are limited to incident-free queue length prediction where traffic arrivals can be readily obtained using detectors. Despite the problems posed by queue overflow, studies addressing queue-overflow issues, or for predicting queue overflows beyond detectors, appear inadequate. This paper describes an advanced methodology which uses a stochastic system modeling approach and random processes for predicting queue lengths beyond detectors in real time. Lane changing is taken into account in developing the queue-overflow prediction model because lane changing accompanies queue overflow in most cases. A discrete-time, nonlinear stochastic system is specified for modeling the queues and lane changes beyond detectors during queue-overflow occurrence. The noise terms of the recursive equations of the model account for the effects of queues and a variety of arriving volumes on vehicular lane-changing maneuvers during queue-overflow occurrence. The unknown traffic arrivals beyond detectors are predicted employing random processes. In addition, a recursive estimation algorithm for predicting real-time queue overflows is developed utilizing the extended Kalman filtering technique. Preliminary test results indicate that the proposed methodology is promising for real-time prediction of queue overflows. The predicted queue overflows can be used not only in understanding the phenomenon of lane traffic patterns during queue-overflow occurrence, but also in developing related advanced technologies such as real-time road traffic congestion control and management systems.
A stochastic modeling approach to real-time prediction of queue overflows (vol 37, pg 97, 2003)
(2003-05-01)
Sheu, JB
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Queue overflow is a critical issue in developing queue prediction technologies for applications in Advanced Transportation Management System (ATMS). Conventional queue prediction methods, however are limited to incident-free queue length prediction where traffic arrivals can be readily obtained using detectors. Despite the problems posed by queue overflow, studies addressing queue-overflow issues, or for predicting queue overflows beyond detectors, appear inadequate. This paper describes an advanced methodology which uses a stochastic system modeling approach and random processes for predicting queue lengths beyond detectors in real time. Lane changing is taken into account in developing the queue-overflow prediction model because lane changing accompanies queue overflow in most cases. A discrete-time, nonlinear stochastic system is specified for modeling the queues and lane changes beyond detectors during queue-overflow occurrence. The noise terms of the recursive equations of the model account for the effects of queues and a variety of arriving volumes on vehicular lane-changing maneuvers during queue-overflow occurrence. The unknown traffic arrivals beyond detectors a-re predicted employing random processes. In addition, a recursive estimation algorithm for predicting real-time queue overflows is developed utilizing the extended Kalman filtering technique. Preliminary test results indicate that the proposed methodology is promising for real-time prediction of queue overflows. The predicted queue overflows can be used not only in understanding the phenomenon of lane traffic patterns during queue-overflow occurrence, but also in developing related advanced technologies such as real-time road traffic congestion control and management systems.
A stochastic optimal control approach to real-time, incident-responsive traffic signal control at isolated intersections
(2002-11-01)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Real-time, incident-responsive traffic control and management is vital to development of advanced incident management systems in ITS. More importantly, it provides, from an academic point of view, the linkages between incident detection, incident management, and traffic signal control. This study explores the application of a stochastic optimal control approach to real-time, incident-responsive traffic control at isolated intersections. In the methodology development, time-varying lane traffic state variables and control variables are specified to characterize sectionwide interlane and intralane traffic states under conditions of lane-blocking incidents. Following specification of system states, we formulated a discrete-time nonlinear stochastic model that comprises four types of equations, namely (1) recursive equations, (2) measurement equations, (3) incident-induced delay equations, and (4) boundary constraints. From the proposed stochastic model we then developed a stochastic optimal control algorithm to update the time-varying control variables and lane traffic state variables in real-time with lane-blocking incidents at isolated intersections. To generate traffic data used in model tests efficiently, we employed an advanced microscopic traffic simulator, Paramics, Version 3.0, which is developed to model and analyze ITS traffic flow conditions. The preliminary test results indicate that the proposed method can accomplish the goal of real-time, incident-responsive traffic signal control. In addition to proposing a new methodology, we hope that this study can initiate investigation into real-time, incident-responsive traffic control and management to achieve the final goal of networkwide incident-responsive, traffic-optimal control for incident management.
A stochastic optimal control approach to real-time, incident-responsive traffic signal control at isolated intersections
(2002-11-01)
Sheu, JB
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Real-time, incident-responsive traffic control and management is vital to development of advanced incident management systems in ITS. More importantly, it provides, from an academic point of view, the linkages between incident detection, incident management, and traffic signal control. This study explores the application of a stochastic optimal control approach to real-time, incident-responsive traffic control at isolated intersections. In the methodology development, time-varying lane traffic state variables and control variables are specified to characterize sectionwide interlane and intralane traffic states under conditions of lane-blocking incidents. Following specification of system states, we formulated a discrete-time nonlinear stochastic model that comprises four types of equations, namely (1) recursive equations, (2) measurement equations, (3) incident-induced delay equations, and (4) boundary constraints. From the proposed stochastic model we then developed a stochastic optimal control algorithm to update the time-varying control variables and lane traffic state variables in real-time with lane-blocking incidents at isolated intersections. To generate traffic data used in model tests efficiently, we employed an advanced microscopic traffic simulator, Paramics, Version 3.0, which is developed to model and analyze ITS traffic flow conditions. The preliminary test results indicate that the proposed method can accomplish the goal of real-time, incident-responsive traffic signal control. In addition to proposing a new methodology, we hope that this study can initiate investigation into real-time, incident-responsive traffic control and management to achieve the final goal of networkwide incident-responsive, traffic-optimal control for incident management.
A stochastic optimal control based approach to real-time incident-responsive local ramp control
(2003)
Sheu, JB
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Cho, YH
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Yan, CJ
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents a stochastic optimal control based methodology for real-time local ramp control in response to: lane-blocking incidents on freeways. A discrete-time nonlinear stochastic system, which characterizes, the time varying relationships among. lane. traffic states, control variables, and point detector data, is proposed. In addition, a stochastic optimal control-based algorithm is developed to update the time-varying ramp metering control variables and incident-induced lane traffic states in real, time. Preliminary test results indicate that the proposed ramp control method permits alleviating incident impacts. efficiently particularly. under low-volume and medium-volume incident, conditions. Moreover, utilizing the proposed method, time-varying lane traffic states together with incident impacts on queue lengths and capacities can be estimated in parallel with incident-responsive ramp control to monitor the, status of incident impact-and provide incident-related traffic. information for further applications, e.g., incident management..
An integrated logistics operational model for green-supply chain management
(2005-07-01)
Sheu, JB
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Chou, YH
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Hu, CC
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents an optimization-based model to deal with integrated logistics operational problems of green-supply chain management (G-SCM). In the proposed methodology, a linear multi-objective programming model is formulated that systematically optimizes the operations of both integrated logistics and corresponding used-product reverse logistics in a given green-supply chain. Factors such as the used-product return ratio and corresponding subsidies from governmental organizations for reverse logistics are considered in the model formulation. Results of numerical studies indicate that using the proposed model, the chain-based aggregate net profits can be improved by 21.1%, compared to the existing operational performance in the particular case studied. © 2004 Elsevier Ltd. All rights reserved.
An integrated logistics operational model for green-supply chain management
(2005-07-01)
Sheu, JB
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Chou, YH
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Hu, CC
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper presents an optimization-based model to deal with integrated logistics operational problems of green-supply chain management (G-SCM). In the proposed methodology, a linear multi-objective programming model is formulated that systematically optimizes the operations of both integrated logistics and corresponding used-product reverse logistics in a given green-supply chain. Factors such as the used-product return ratio and corresponding subsidies from governmental organizations for reverse logistics are considered in the model formulation. Results of numerical studies indicate that using the proposed model, the chain-based aggregate net profits can be improved by 21.1%, compared to the existing operational performance in the particular case studied. © 2004 Elsevier Ltd. All rights reserved.
Locating manufacturing and distribution centers: An integrated supply chain-based spatial interaction approach
(2003-09-01)
Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study investigates the facility location problem of transnational personal computer (PC) manufacturing for the domestic market of China. An integrated supply chain-based spatial interaction model is formulated to determine facility locations of the transnational PC manufacturing centers and regional product distribution centers in China, with the goal of maximizing the potential rate of return on facility investment. The numerical results show that the Shanghai municipality is ranked highest for siting both the manufacturing and distribution centers for a transnational PC manufacturing enterprise. (C) 2003 Elsevier Ltd. All rights reserved.
Relationships of channel power, noncoercive influence strategies, climate, and solidarity: A real case study of the Taiwanese PDA industry
(2005-07-01)
Hu, TL
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Sheu, JB
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
The management of channel relations has a significant impact on a firm's operational competitiveness; however, there is a lack of published research to better understand the linkages between channel relationships and channel power, noncoercive influence strategies, as well as channel climate and channel solidarity. This paper develops a model showing the linkages among these dimensions of channel relationships. Using linear structural relations (LISREL), a model of the Taiwanese personal digital assistant industry is developed to illustrate these interactions. The corresponding empirical test results indicate that channel climate has a significant impact on channel solidarity; however, this impact may be mitigated by both channel power and the use of noncoercive influence strategies. In addition, both mutual trust among channel members and continuity of the relationship have a positive influence on channel solidarity. Channel members with relatively more power appear able to determine the degree of channel solidarity through the use of effective noncoercive influence strategies. (c) 2004 Elsevier Inc. All rights reserved.
Stochastic modeling and real-time prediction of incident effects on surface street traffic congestion
(2004-05-01)
Sheu, JB
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Chou, YH
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Chen, A
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Modeling and real-time prediction of incident-induced time-varying lane traffic states, e.g., mandatory lane-changing fractions, queue lengths, and delays are vital to investigate the time-varying incident effects on traffic congestion in both the spatial and temporal domains. This paper presents a discrete-time nonlinear stochastic model to characterize the time-varying relationships of specified lane traffic states under the condition of lane-blocking incidents on surface streets. The proposed stochasti: model is composed of four types of equations: (1) recursive equations, (2) measurement equations, (3) delay-aggregation equations, and (4) boundary constraints. In addition, a recursive estimation algorithm is developed for real-time prediction of the specified time-varying lane traffic states. The proposed method Is tested with simulated data generated using the Paramics traffic simulator. The preliminary tests indicate the capability of the proposed method to estimate incident effects on surface street traffic congestion in real time. We also expect that this study can provide real-time incident-related traffic information with benefits both for understanding the impact of incidents on non-recurrent traffic congestion of surface streets, and for developing advanced incident-responsive traffic control and management technologies. (C) 2003 Elsevier Inc. All rights reserved.
Stochastic system modeling and optimal control of incident-induced traffic congestion
(2003-09-01)
Sheu, JB
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Chou, YH
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Weng, MC
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Incident-induced traffic congestion is a critical issue in formulating urban traffic congestion problems, and also a major cause that contributes to the invalidity of traffic signal control. This paper presents a prototype of real-time local signal control method, and explores its applicability in alleviating incident-induced traffic congestion on the roadway between two adjacent intersections for incident management. The architecture includes two major parts: (1) formulating time-varying lane traffic state variables and control variables under conditions of lane-blocking incidents with a discrete-time non-linear stochastic model, and (2) developing a real-time control algorithm for predicting dynamically control variables. To generate efficiently traffic data used in model tests, we employed the Paramics microscopic traffic simulator, which is developed to model and analyze ITS traffic flow conditions. According to the measures of two proposed space-based incident-impact indexes, the preliminary test results indicate the superiority of the proposed real-time signal control method in comparison with fixed-time signal control modes which are currently used at the study site. We do expect that this study can stimulate research on incident management, and extend to network-wide incident-responsive traffic control for the development of advanced traffic management systems (ATMS). (C) 2003 Elsevier Ltd. All rights reserved.