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Real-time optimization of train regulation and passenger flow control for urban rail transit network under frequent disturbances

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年 168卷

作者： Yuan, Yin Li, Shukai Yang, Lixing Gao, Ziyou Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

Urban rail transit networks face frequent delays and oversaturation resulting from unexpected disturbances and high demands during rush hours, which inevitably leads to unstable train operations, poor service experiences, and potential accidents on crowded platforms. This paper explores the train regulation and passenger flow control strategies for large-scale urban rail transit networks. Specifically, we develop a mixed-integer nonlinear programming (MINLP) formulation to improve the punctuality and regularity in train operations, reduce the passenger waiting time, and alleviate the passenger flow burden of platforms, where the dynamic coupling interactions among network-wide passengers, trains and stations are systematically considered. To reduce the computational complexity and satisfy real-time requirements, we particularly devise a real-time optimization approach based on iterative nonlinear programming (INP) combined with Lagrangian relaxation (LR) under the rolling horizon (RH) framework, which effectively disposes of the intractable nonconvexity and constructs the desirable properties of decomposability and parallelism. The original problem is transformed into a sequence of line -level subproblems that can be solved quickly, so as to circumvent the computational burden. Moreover, to verify the effectiveness of our approach, we apply it to address numerical examples on a simplified network and the real-world Beijing Subway network. The realistic case studies illustrate that the proposed approach can reduce the train deviation from the original timetable, the passenger waiting time, and the passenger accumulation risk on the platform, by around 84.92%, 30.34% and 61.42% in comparison with the common rule-based strategy. Additionally, the computation time for the realistic large-scale experiment is acceptable for a real-time implementation.

关键词： Urban rail transit networks Train regulation Passenger flow control Lagrangian relaxation mixed-integer nonlinear programming

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Modern tools for the time-discrete dynamics and optimization of gene-environment networks

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COMMUNICATIONS IN nonlinear SCIENCE AND NUMERICAL SIMULATION 2011年第12期16卷 4768-4779页

作者： Defterli, Ozlem Fuegenschuh, Armin Weber, Gerhard Wilhelm Cankaya Univ Fac Art & Sci Dept Math & Comp Sci TR-06530 Ankara Turkey Zuse Inst Berlin Dept Optimizat D-14195 Berlin Germany Middle E Tech Univ Inst Appl Math TR-06531 Ankara Turkey

In this study, we discuss the models of genetic regulatory systems, so-called gene-environment networks. The dynamics of such kind of systems are described by a class of time-continuous ordinary differential equations having a general form (E) over dot = M(E)E, where E is a vector of gene-expression levels and environmental factors and M(E) is the matrix having functional entries containing unknown parameters to be optimized. Accordingly, time-discrete versions of that model class are studied and improved by introducing 3rd-order Heun's method and 4th-order classical Runge-Kutta method. The corresponding iteration formulas are derived and their matrix algebras are obtained. After that, we use nonlinear mixed-integer programming for the parameter estimation in the considered model and present the solution of a constrained and regularized given mixed-integer problem as an example. By using this solution and applying both the new and existing discretization schemes, we generate corresponding time-series of gene-expressions for each method. The comparison of the experimental data and the calculated approximate results is additionally done with the help of the figures to exercise the performance of the numerical schemes on this example. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Gene-networks Regulatory systems Dynamical systems Discretization mixed-integer nonlinear programming

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Co-design of stabilisation and transmission scheduling for wireless control systems

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IET CONTROL THEORY AND APPLICATIONS 2017年第11期11卷 1767-1778页

作者： Lyu, Ling Chen, Cailian Hua, Cunqing Zhu, Shanying Guan, Xinping Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Informat Secur Engn Shanghai 200240 Peoples R China

Wireless control system (WCS) refers to the feedback control system with state and (or) control information transmitted over wireless channels. The control system stability is severely affected by the wireless transmission reliability, which in turn relies heavily on the scheduling of limited wireless communication resources, such as channel, time and power. Therefore, co-design of control stabilisation and transmission scheduling is of vital importance. In this study, the authors firstly explore the effect of wireless transmission reliability on control performance for a WCS with multiple subsystems, local sensors and a remote combination of controller-scheduler. Then a feedback control method is designed to mitigate the impact of unreliable transmission in the loop of sensor-to-controller and controller-to-actuator. Stabilisation and transmission scheduling are co-designed to stabilise the system and minimise the control-communication cost by solving a mixed-integer non-linear programming problem. A decomposition scheme is finally proposed to optimise the control performance by minimising the gap with standard linear quadratic regulator controller as well as the communication cost by allocating the transmission channels, time-slots and power. The effectiveness and advantage of the proposed scheme are demonstrated by the simulation results for a slab temperature control system in hot rolling process.

关键词： hot rolling slabs temperature control telecontrol feedback stability control system synthesis linear quadratic control scheduling integer programming nonlinear programming control stabilization transmission scheduling wireless control system WCS feedback control system design control system stability wireless transmission reliability mixed-integer nonlinear programming decomposition scheme linear quadratic regulator controller slab temperature control system hot rolling process

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Global optimization algorithm for capacitated multi-facility continuous location-allocation problems

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第4期71卷 871-889页

作者： Lara, Cristiana L. Trespalacios, Francisco Grossmann, Ignacio E. Carnegie Mellon Univ Dept Chem Engn 5000 Forbes Ave Pittsburgh PA 15213 USA ExxonMobil Res & Engn Co Corp Strateg Res 1545 Route 22 East Annandale NJ 08801 USA

In this paper we propose a nonlinear Generalized Disjunctive programming model to optimize the 2-dimensional continuous location and allocation of the potential facilities based on their maximum capacity and the given coordinates of the suppliers and customers. The model belongs to the class of Capacitated Multi-facility Weber Problem. We propose a bilevel decomposition algorithm that iteratively solves a discretized MILP version of the model, and its nonconvex NLP for a fixed selection of discrete variables. Based on the bounding properties of the subproblems, -convergence is proved for this algorithm. We apply the proposed method to random instances varying from 2 suppliers and 2 customers to 40 suppliers and 40 customers, from one type of facility to 3 different types, and from 2 to 32 potential facilities. The results show that the algorithm is more effective at finding global optimal solutions than general purpose global optimization solvers tested.

关键词： Location-allocation problem Weber problem Nonconvex optimization Generalized disjunctive programming mixed-integer nonlinear programming

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Selecting different raw materials for methanol production using an MINLP model

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JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2014年 19卷 221-227页

作者： Kralj, Anita Kovac Univ Maribor Fac Chem & Chem Engn SLO-2000 Maribor Slovenia

This paper aims at selecting different raw materials, using an MINLP (mixed-integer nonlinear programming) model, when considering the usage of more favourable raw materials for methanol production. The best selection of raw material alternatives was sought for methanol production. Methanol is produced from synthesis gas that is produced from different raw materials - natural gas or biogas. The basic starting point when comparing them is the same mass inlet flow rate for both raw materials. Methanol production was simulated for both natural gas or biogas as the raw material, using an Aspen Plus simulator with a real chemical thermodynamic. Methanol production can be enlarged by simultaneous structuring such as selecting the usage of more favourable raw materials, and parameter optimisation using the MINLP. The selection of raw methanol with optimal parameters has the greatest impact on higher methanol production. Optimal methanol conversion can take place during this operation, by applying optimal parametric data within a reformer unit (temperature = 840 degrees C and pressure = 8 bar), using natural gas. The optimal production of methanol from natural gas was 17 510 kg/h under optimal parameters for 8.4% higher production than under existing parameters. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Methanol production Natural gas Biogas Mathematical model mixed-integer nonlinear programming

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The Location Routing Problem of the Car-Sharing System with Autonomous Electric Vehicles

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KSCE JOURNAL OF CIVIL ENGINEERING 2021年第8期25卷 3107-3120页

作者： Ma, Bingshan Hu, Dawei Wu, Xue Changan Univ Sch Automobile Xian 710064 Peoples R China Changan Univ Sch Transportat Engn Xian 710064 Peoples R China

Car-sharing, electrification, and autonomous driving are greatly revolutionizing the future of the transportation system. This study proposes a location routing problem for the car-sharing system with autonomous electric vehicles to determine optimal station location and vehicle routing, where each station is both a depot and a charging station. A mathematical model is formulated and then extended to three variants, while simultaneously considering different recharging and service options. The proposed mixed-integer nonlinear models are separately solved by general algebraic modeling system (GAMS) and genetic algorithm (GA), and the efficiency of the GA is demonstrated. The comparative experimental results of instances are presented, and the benefits of allowing partial recharge are obtained. More significant savings in cost can be achieved if partial service is simultaneously allowed. Furthermore, the trade-off between the operator's interests and the interests of users, as well as the operator's immediate profits and future profits, are explored through sensitivity analysis.

关键词： Shared autonomous vehicles Electric vehicles Location routing problem mixed-integer nonlinear programming Genetic algorithm (GA)

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Symmetry-exploiting cuts for a class of mixed-0/1 second-order cone programs

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DISCRETE OPTIMIZATION 2014年 13卷 23-35页

作者： Drewes, Sarah Pokutta, Sebastian Georgia Inst Technol ISyE Atlanta GA 30332 USA

We will analyze mixed-0/1 second-order cone programs where the continuous and binary variables are solely coupled via the conic constraints. We devise a cutting-plane framework based on an implicit Sherali-Adams reformulation. The resulting cuts are very effective as symmetric solutions are automatically cut off and each equivalence class of 0/1 solutions is visited at most once. Further, we present computational results showing the effectiveness of our method and briefly sketch an application in optimal pooling of securities. (C) 2014 Elsevier B.V. All rights reserved.

关键词： mixed-integer nonlinear programming Cutting planes Second order cone programming Outer approximation

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Gap inequalities for non-convex mixed-integer quadratic programs

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OPERATIONS RESEARCH LETTERS 2011年第5期39卷 297-300页

作者： Galli, Laura Kaparis, Konstantinos Letchford, Adam N. Univ Lancaster Dept Management Sci Lancaster LA1 4YW England Univ Bologna DEIS I-40136 Bologna Italy

Laurent and Poljak introduced a very general class of valid linear inequalities, called gap inequalities, for the max-cut problem. We show that an analogous class of inequalities can be defined for general non-convex mixed-integer quadratic programs. These inequalities dominate some inequalities arising from a natural semidefinite relaxation. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Max-cut problem mixed-integer nonlinear programming Polyhedral combinatorics

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A comparative study of SQP-type algorithms for nonlinear and nonconvex mixed-integer optimization

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MATHEMATICAL programming COMPUTATION 2012年第4期4卷 383-412页

作者： Exler, Oliver Lehmann, Thomas Schittkowski, Klaus Univ Bayreuth Dept Comp Sci D-95440 Bayreuth Germany Konrad Zuse Zentrum ZIB D-14195 Berlin Germany

We present numerical results of a comparative study of codes for nonlinear and nonconvex mixed-integer optimization. The underlying algorithms are based on sequential quadratic programming (SQP) with stabilization by trust-regions, linear outer approximations, and branch-and-bound techniques. The mixed-integer quadratic programming subproblems are solved by a branch-and-cut algorithm. Second order information is updated by a quasi-Newton update formula (BFGS) applied to the Lagrange function for continuous, but also for integer variables. We do not require that the model functions can be evaluated at fractional values of the integer variables. Thus, partial derivatives with respect to integer variables are replaced by descent directions obtained from function values at neighboring grid points, and the number of simulations or function evaluations, respectively, is our main performance criterion to measure the efficiency of a code. Numerical results are presented for a set of 100 academic mixed-integer test problems. Since not all of our test examples are convex, we reach the best-known solutions in about 90 % of the test runs, but at least feasible solutions in the other cases. The average number of function evaluations of the new mixed-integer SQP code is between 240 and 500 including those needed for one-or two-sided approximations of partial derivatives or descent directions, respectively. In addition, we present numerical results for a set of 55 test problems with some practical background in petroleum engineering.

关键词： MINLP mixed-integer nonlinear programming SQP Sequential quadratic programming Trust region method Linear outer approximation MIQP mixed-integer quadratic programming Numerical algorithms Performance evaluation mixed-integer test problems Engineering optimization

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Turnpike Properties in Discrete-Time mixed-integer Optimal Control

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IEEE CONTROL SYSTEMS LETTERS 2020年第3期4卷 704-709页

作者： Faulwasser, Timm Murray, Alexander TU Dortmund Univ Inst Energy Syst Energy Efficiency & Energy Econ D-44227 Dortmund Germany Karlsruhe Inst Technol Inst Automat & Appl Informat D-76131 Karlsruhe Germany

This note discusses properties of parametric discrete-time mixed-integer Optimal Control Problems (MIOCPs) as they often arise in model predictive control with discrete controls. We argue that, in want for a handle on similarity properties of parametric MIOCPs, the turnpike phenomenon known in optimal control is helpful. We provide sufficient turnpike conditions based on a dissipativity notion of MIOCPs, and we prove that the turnpike phenomenon allows specific and accurate guesses for the discrete controls. We also derive an easily checkable sufficient condition for dissipativity of linear-quadratic MIOCPs. Moreover, we show how the turnpike property can be used to derive efficient node-weighted branch-and-bound schemes tailored to parametric MIOCPs. We draw upon numerical examples to illustrate our findings.

关键词： Optimal control Steady-state Predictive control Optimization Sensitivity Economics Indexes Optimal control dissipativity mixed-integer optimization mixed-integer nonlinear programming

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