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Dive into the research topics where Shukai Li is active.

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Featured researches published by Shukai Li.


Information Sciences | 2015

On distribution function of the diameter in uncertain graph

Yuan Gao; Lixing Yang; Shukai Li; Samarjit Kar

In uncertain graphs, the existence of some edges is not predetermined. The diameter of an uncertain graph is essentially an uncertain variable, which indicates the suitability for investigation of its distribution function. The main focus of this paper is to propose an algorithm to determine the distribution function of the diameter of an uncertain graph. We first discuss the characteristics of the uncertain diameter, and the distribution function is derived. An efficient algorithm is designed based on Floyds algorithm. Further, some numerical examples are illustrated to show the efficiency and application of the algorithm.


IEEE Transactions on Control Systems and Technology | 2016

Robust Model Predictive Control for Train Regulation in Underground Railway Transportation

Shukai Li; Bart De Schutter; Lixing Yang; Ziyou Gao

This brief investigates the robust model predictive control (MPC) for train regulation in underground railway transportation. By considering the uncertain passenger arrival flow, a constrained state-space model for the train traffic of a metro loop line is developed. The goal of this brief is to design a state feedback control law at each decision step to optimize a metro system cost function subject to safety constraints on the control input. Based on Lyapunov function theory, the problem of optimizing an upper bound on the system cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities. Moreover, for the inevitable disturbances leading to the delays, the robust MPC strategy of train regulation is designed for a metro loop line such that it ensures the minimization of an upper bound on metro system cost function, and meanwhile guarantees a disturbance attenuation level with respect to the disturbances. Numerical examples are given to illustrate the effectiveness of the proposed methods.


Journal of intelligent systems | 2015

A Coordinated Routing Model with Optimized Velocity for Train Scheduling on a Single-Track Railway Line

Lixing Yang; Shukai Li; Yuan Gao; Ziyou Gao

Train scheduling aims to seek a set of space‐time paths for multiple trains on a railway line such that resources can be utilized efficiently with respect to prespecified criteria. By representing the train trajectory through a time‐space path in its space‐time network, this paper proposes an integer programming model for train scheduling on a single‐track railway line, in which velocity choice is particularly considered to further decrease the expected energy consumption and interactions between different trains, and the link energy consumption is derived by the Davis formula with respect to different train speeds. The proposed model is implemented in the GAMS optimization software to solve an approximate optimal solution. Numerical examples show that the optimal timetable with optimized velocities can further decrease the energy consumption and coupling effects in comparison to the fixed velocity based schedule.


Isa Transactions | 2014

Stabilization strategies of a general nonlinear car-following model with varying reaction-time delay of the drivers

Shukai Li; Lixing Yang; Ziyou Gao; Keping Li

In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods.


Information Sciences | 2016

Robust train regulation for metro lines with stochastic passenger arrival flow

Shukai Li; Lixing Yang; Ziyou Gao; Keping Li

A train traffic model of metro line with stochastic passenger arrival flow is developed.The stochastic stability condition of metro line is given in terms of LMIs.Robust train regulation strategy is designed to reduce the total delays of the trains.The proposed method significantly improves the operation efficiency of the metro system. This paper investigates the robust train regulation problem for metro lines with a stochastic passenger arrival flow. The passenger arrival flow is assumed to be dependent on a discrete Markovian process. A constrained state-space model for the train traffic of a metro-line operation is developed from a system-theoretic standpoint. According to stochastic stability theory, we give a sufficient condition for the existence of state-feedback control as the train regulation strategy in terms of linear matrix inequalities, which ensures the stochastic stability of the train traffic of metro lines. By considering the uncertain disturbances to the train operation, a robust train regulation strategy that guarantees that the practical train timetable tracks the nominal timetable with a disturbance attenuation level is designed, and the total delays of the trains at each station are reduced. Moreover, a nonlinear optimization problem is formulated to determine the optimal robust train regulation strategy that ensures the minimization of the disturbance attenuation level. Numerical examples are given to illustrate the effectiveness of the proposed methods.


IEEE Transactions on Intelligent Transportation Systems | 2016

Optimal Guaranteed Cost Cruise Control for High-Speed Train Movement

Shukai Li; Lixing Yang; Ziyou Gao; Keping Li

In this paper, the optimal guaranteed cost cruise control for high-speed train movement with uncertain parameters and control constraints is investigated. Sufficient condition for the existence of guaranteed cost cruise control law is given in terms of linear matrix inequalities, under which each car of the high-speed train tracks the desired speed, the relative spring displacement is stable at the equilibrium state, and meanwhile an upper bound of the train performance is guaranteed. Moreover, a convex optimization problem is formulated to determine the optimal guaranteed cost control law that minimizes an upper bound on the train performance (energy consumption and tracking error). Numerical examples are given to illustrate the effectiveness of the proposed methods.


Journal of the Operational Research Society | 2018

Joint optimization model for train scheduling and train stop planning with passengers distribution on railway corridors

Jianguo Qi; Shukai Li; Yuan Gao; Kai Yang; Pei Liu

Aiming to provide a more practical modeling framework for railway optimization problem, this paper investigates the joint optimization model for train scheduling, train stop planning and passengers distributing by considering the passenger demands over each origin and destination (OD) pair on a high-speed railway corridor. Specifically, through introducing new decision variables associated with the number of passengers distributed in each train over each OD pair and formulating the connection constraints between the train stop plan and passenger distributions, the total travel time of all the trains is firstly adopted as the objective function to optimize the train stop plan and timetable with the passenger demands being guaranteed. Then, based on the generated train stop plan and timetable, the passenger distribution plan is further optimized with the purpose of minimizing the total travel time of all the passengers. Finally, the effectiveness and efficiency of the proposed approaches are verified by the obtained train stop plans, timetables and passenger distribution plans for a sample railway corridor and Wuhan–Guangzhou high-speed railway corridor. The computational results showed that the proposed methods can effectively obtain the train stop plan, timetable and passenger distribution plan at the same time.


Engineering Optimization | 2017

Designing train-speed trajectory with energy efficiency and service quality

Jiannan Jia; Kai Yang; Lixing Yang; Yuan Gao; Shukai Li

ABSTRACT With the development of automatic train operations, optimal trajectory design is significant to the performance of train operations in railway transportation systems. Considering energy efficiency and service quality, this article formulates a bi-objective train-speed trajectory optimization model to minimize simultaneously the energy consumption and travel time in an inter-station section. This article is distinct from previous studies in that more sophisticated train driving strategies characterized by the acceleration/deceleration gear, the cruising speed, and the speed-shift site are specifically considered. For obtaining an optimal train-speed trajectory which has equal satisfactory degree on both objectives, a fuzzy linear programming approach is applied to reformulate the objectives. In addition, a genetic algorithm is developed to solve the proposed train-speed trajectory optimization problem. Finally, a series of numerical experiments based on a real-world instance of Beijing–Tianjin Intercity Railway are implemented to illustrate the practicability of the proposed model as well as the effectiveness of the solution methodology.


fuzzy systems and knowledge discovery | 2015

Robust train timetabling problem with optimized train stop plan

Jianguo Qi; Lixing Yang; Yuan Gao; Shukai Li

Simultaneously considering train timetabling problem and stop planning problem with uncertain travel time, this paper proposes a collaborative model, which can be decomposed into two stages. Specifically, in the first stage, the travel time of each train on each link is taken as a stochastic variable, which is the sum of a minimum travel time (a constant variable) and disturbance time (a stochastic variable). Through embedding the train stop planning process into the train timetabling problem, the train stop plan and train timetable under different scenarios can be generated/optimized in the first stage. In the second stage, we treat the travel time of each train on each link as a decision variable, which is restricted to be no less than the minimum travel time. Then, based on the train stop plan and train timetable generated in the first stage, an optimal robust train timetable and train stop plan can be obtained, in which the sum of variance between the robust timetable and each timetable generated in the first stage is minimum. The optimization software GAMS with CPLEX and BARON solvers are used to solve the proposed model and generate approximate optimal solutions. Finally, an experiment is implemented to show the effectiveness and efficiency of our proposed method.


Transportation Research Part C-emerging Technologies | 2014

Robust sampled-data cruise control scheduling of high speed train

Shukai Li; Lixing Yang; Keping Li; Ziyou Gao

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Lixing Yang

Beijing Jiaotong University

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Ziyou Gao

Beijing Jiaotong University

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Yuan Gao

Beijing Jiaotong University

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Jianguo Qi

Beijing Jiaotong University

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Keping Li

Beijing Jiaotong University

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Kai Yang

Beijing Jiaotong University

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Pei Liu

Beijing Jiaotong University

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Maged Dessouky

University of Southern California

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Xuesong Zhou

Arizona State University

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Jiannan Jia

Beijing Jiaotong University

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