Transportation Research Part B-methodological, Sep 1, 2015
ABSTRACT The inconsistence between system optimality and user optimality represents one of the ke... more ABSTRACT The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.
Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many are... more Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many areas including marketing research, clinical trials, and biomedical studies. Inference can be conducted using maximum likelihood approach if assuming Normal distributions on the random effects. However, in many applications of economy, business and medicine, it is often essential to impose constraints on the regression parameters after taking their real-world interpretations into account. Therefore, in this paper we extend the unconstrained LME models to allow for sign constraints on its overall coefficients. We propose to assume a symmetric doubly truncated Normal (SDTN) distribution on the random effects instead of the unconstrained Normal distribution which is often found in classical literature. With the aforementioned change, difficulty has dramatically increased as the exact distribution of the dependent variable becomes analytically intractable. We then develop likelihood-based appro...
Transportation Research Part B: Methodological, 2015
ABSTRACT The inconsistence between system optimality and user optimality represents one of the ke... more ABSTRACT The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.
A linear complementarity system (LCS) is a special hybrid system which combines a linear ordinary... more A linear complementarity system (LCS) is a special hybrid system which combines a linear ordinary differential equation and a finite-dimensional linear complementarity problem. This paper reviews the recent progress in time-stepping methods for solving the LCS. In particular we focus on time-stepping schemes for passive LCSs and linear quadratic optimal control problems with joint polyhedral control and state constraints. Convergence results are presented for both cases.
ABSTRACT In this paper we study the one commodity pickup-and-delivery traveling salesman problem ... more ABSTRACT In this paper we study the one commodity pickup-and-delivery traveling salesman problem with restricted depot (1-PDTSP-RD), which is a generalization of the classical traveling salesman problem (TSP). We first introduce a polynomial size integer programming formulation for the problem and then study the feasibility issue which is shown to be \(\mathcal {NP}\)-complete by itself. In particular, we prove sufficient conditions for the feasibility of the problem and provide a polynomial algorithm to find a feasible solution. We also develop a bound on the cost of the 1-PDTSP-RD solution in terms of the cost of the TSP solution. Based on this bound, we provide a heuristic algorithm to solve the 1PDTSP-RD. Extensive numerical experiments are performed to evaluate the efficiency of both the exact and approximation algorithms.
18th International Conference on Pattern Recognition (ICPR'06), 2006
We introduce an approach for model-based sequence clustering that addresses several drawbacks of ... more We introduce an approach for model-based sequence clustering that addresses several drawbacks of existing al-gorithms. The approach uses a combination of Hidden Markov Models (HMMs) for sequence estimation and Dy-namic Time Warping (DTW) for hierarchical clustering, ...
2011 IEEE International Conference on Automation Science and Engineering, 2011
ABSTRACT Chlamydia trachomatis infection, a major sexually transmitted disease, affects millions ... more ABSTRACT Chlamydia trachomatis infection, a major sexually transmitted disease, affects millions of people worldwide. A key public health challenge in managing such a transmitted disease is identifying infected but asymptomatic individuals so that they can be treated with antibiotics. Effectively resolving such a challenge will benefit both treated individuals (by improving quality of life) and the entire population (through reduced transmission). We adapt a well-established SEIRS (susceptible-exposed-infected-recovered-susceptible) model to evaluate the cost and effectiveness of different coverage levels of screening. To find the optimal screening rate, we formulate the question as a parameter optimization problem of ordinary differential equations and then apply a line search method which exhibits fast convergence. The numerical results as well as sensitivity analysis are presented in the paper.
Transportation Research Part B-methodological, Sep 1, 2015
ABSTRACT The inconsistence between system optimality and user optimality represents one of the ke... more ABSTRACT The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.
Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many are... more Linear Mixed Effects (LME) models have been widely applied in clustered data analysis in many areas including marketing research, clinical trials, and biomedical studies. Inference can be conducted using maximum likelihood approach if assuming Normal distributions on the random effects. However, in many applications of economy, business and medicine, it is often essential to impose constraints on the regression parameters after taking their real-world interpretations into account. Therefore, in this paper we extend the unconstrained LME models to allow for sign constraints on its overall coefficients. We propose to assume a symmetric doubly truncated Normal (SDTN) distribution on the random effects instead of the unconstrained Normal distribution which is often found in classical literature. With the aforementioned change, difficulty has dramatically increased as the exact distribution of the dependent variable becomes analytically intractable. We then develop likelihood-based appro...
Transportation Research Part B: Methodological, 2015
ABSTRACT The inconsistence between system optimality and user optimality represents one of the ke... more ABSTRACT The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.
A linear complementarity system (LCS) is a special hybrid system which combines a linear ordinary... more A linear complementarity system (LCS) is a special hybrid system which combines a linear ordinary differential equation and a finite-dimensional linear complementarity problem. This paper reviews the recent progress in time-stepping methods for solving the LCS. In particular we focus on time-stepping schemes for passive LCSs and linear quadratic optimal control problems with joint polyhedral control and state constraints. Convergence results are presented for both cases.
ABSTRACT In this paper we study the one commodity pickup-and-delivery traveling salesman problem ... more ABSTRACT In this paper we study the one commodity pickup-and-delivery traveling salesman problem with restricted depot (1-PDTSP-RD), which is a generalization of the classical traveling salesman problem (TSP). We first introduce a polynomial size integer programming formulation for the problem and then study the feasibility issue which is shown to be \(\mathcal {NP}\)-complete by itself. In particular, we prove sufficient conditions for the feasibility of the problem and provide a polynomial algorithm to find a feasible solution. We also develop a bound on the cost of the 1-PDTSP-RD solution in terms of the cost of the TSP solution. Based on this bound, we provide a heuristic algorithm to solve the 1PDTSP-RD. Extensive numerical experiments are performed to evaluate the efficiency of both the exact and approximation algorithms.
18th International Conference on Pattern Recognition (ICPR'06), 2006
We introduce an approach for model-based sequence clustering that addresses several drawbacks of ... more We introduce an approach for model-based sequence clustering that addresses several drawbacks of existing al-gorithms. The approach uses a combination of Hidden Markov Models (HMMs) for sequence estimation and Dy-namic Time Warping (DTW) for hierarchical clustering, ...
2011 IEEE International Conference on Automation Science and Engineering, 2011
ABSTRACT Chlamydia trachomatis infection, a major sexually transmitted disease, affects millions ... more ABSTRACT Chlamydia trachomatis infection, a major sexually transmitted disease, affects millions of people worldwide. A key public health challenge in managing such a transmitted disease is identifying infected but asymptomatic individuals so that they can be treated with antibiotics. Effectively resolving such a challenge will benefit both treated individuals (by improving quality of life) and the entire population (through reduced transmission). We adapt a well-established SEIRS (susceptible-exposed-infected-recovered-susceptible) model to evaluate the cost and effectiveness of different coverage levels of screening. To find the optimal screening rate, we formulate the question as a parameter optimization problem of ordinary differential equations and then apply a line search method which exhibits fast convergence. The numerical results as well as sensitivity analysis are presented in the paper.
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