DOCSLIB.ORG

5Th International Seminar on Railway Operations Modelling and Analysis - Railcopenhagen

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
5Th International Seminar on Railway Operations Modelling and Analysis - Railcopenhagen 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen Monday 13 May 2013 - Wednesday 15 May 2013 Technical University of Denmark Book of abstracts 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Tuesday 24 June 2014 Book of abstracts 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Book of abstracts Page 2 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Book of abstracts Book of abstracts 5th International Seminar on Railway Operations Modelling and Analysis RailCopenhagen2013 13-15 May, 2013 Page 3 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Book of abstracts 2 - Stability of railway dispatching solutions under a stochastic and dynamic environment Presenter: Dr. QUAGLIETTA, Egidio (Delft, University of Technology); Dr. GOVERDE, Rob M.P. (Delft, University of Technology) Railway traffic is strongly influenced by random disturbances during operations which cause deviations from the original schedule and thereby reducing performances. In order to cope with small perturbations, the design of a robust timetable can be an effective solution; but if larger disturbances or service disruptions are observed, it is necessary to adopt real-time dispatching measures to reschedule (reorder, retime or reroute) train services into new updated conflict-free train path plans. The rescheduling process involves a first phase in which the traffic state is predicted over a pre-set time horizon (called prediction horizon) on the basis of current traffic information (e.g. train positions, speeds) that is communicated at irregular time intervals to the Traffic Management System. If conflicting train paths are detected, a second phase is activated to compute suitable solutions addressed to restore planned operations as quick as possible or to minimize impacts of conflicts on service availability. The effectiveness of a rescheduling decision not only depends on the operational strategy identified to solve detected conflicts, but also on the actual traffic state that holds when such solution is implemented. During the time lag between the last field measurement and the practical application of the rescheduling plan (the so called control delay), the traffic state could evolve differently from the prediction due to its stochastic and dynamic nature. The control delay depends on different factors such as the type of monitoring system installed (e.g. train describers, GSM-R) and the frequency of train data updates to dispatching centres, the time to predict conflicts and elaborate a new suitable scheduling strategy, as well as the time needed by dispatchers to evaluate and communicate such solution to the interlocking system and possibly to the train. Intuitively, the larger such delay the higher is the probability that a certain rescheduling measure will be ineffective and even counterproductive for mitigating effects of detected conflicts. In this case, the solution should be recomputed and adjusted accordingly to current conditions of the network. During real operations, control measures cannot be updated and implemented continuously, since from one side there are constraints on technical times to obtain and transfer new plans to the system, while from the other side there is a practical unfeasibility for dispatchers to manage different alternatives in short time periods. In this context, particular attention must be paid to the stability of rescheduling plans. A plan can be defined as stable when its (initial) structure is invariant to random perturbations occurring on the network within a given time period Δt. In other words, the first part of a stable control strategy is the same for successive computations after each Δt with respect to updated traffic information and can thus be confidently implemented. In literature only little work [1] deal with stability of dispatching measures under a stochastic and dynamic environment. Instead, numerous approaches have been proposed so far [2, 3, 4] for efficiently generating optimal schedules to minimize train delays, through an open-loop optimization process which primarily involves assumptions of certain and deterministic conditions. In practice, since no advanced decision support tool is generally available, traffic controllers take real-time decisions according to their own experience or rules-of-thumb, without taking into account potential new conflicts due to the stochastic evolution of traffic states [5]. This paper addresses the stability of real-time schedules within a stochastic and dynamic system. To this aim an innovative framework is developed which integrates the Alternative-Graph based tool ROMA [4] for computing optimal rescheduling plans with a stochastic microscopic model for simulating railway traffic. Optimal plans returned by ROMA for a given perturbed scenario are transferred to and implemented in the simulator as if this latter is the real field. An application to a real case study is performed to evaluate open-loop optimization solutions while considering random and dynamic changes in traffic conditions during the control delay. In particular an investigation is conducted to understand how sensitive schedule stability is with respect to the control delay and the prediction horizon. This also gives insight in the maximal time before occurrence of the expected conflicts that a stable solution can be pursued. Then optimal rescheduling plans are recomputed at regular time intervals with respect to current traffic states, assuming continuous updates of train information and the minimum technically possible control delay to put such plans into operation. These successive solutions are compared in order to understand how the optimal control strategy changes over time due to stochastic disturbances and dynamic evolution of traffic behaviour. Understanding the stability of successive dispatching solutions is a first step into closed-loop railway traffic control and is preparatory to an effective management of real-time perturbations. In a rolling horizon approach the stable part of a dispatching plan can be implemented at some point with confidence that this will be the optimal choice for any control decisions at a later stage. References [1] Meng L., Zhou X., Robust Single-Track Train Dispatching Model Under A Dynamic And Stochastic Environment: A Scenario-Based Rolling Horizon Solution Approach, Transportation Research Part B, Vol. 45, pp.1080-1102, 2011. [2] Dorfman M.J., Medanic J., Scheduling Trains On A Railway Network Using A Discrete Event Model Of A Railway Traffic, Transportation Research Part B, Vol. 38, pp. 81-98, 2004. [3] Tornquist J., Persson J., N-Tracked Railway Traffic Re-Scheduling During Disturbances, Transportation Research Part B, Vol. 41, pp.342-362, 2007. [4] D’Ariano A., Improving Real-Time Train Dispatching: Models, Algorithms And Applications, PhD Thesis, Delft University of Technology, the Netherlands, 2008. [5] Sahin I., Railway Traffic And Train Scheduling Based On Inter-Train Conflict Management, Transportation Research Part B, Vol.33, pp. 511-534, 1999. Page 4 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Book of abstracts Page 5 5th International Seminar on Railway Operations Modelling and Analysis - RailCopenhagen / Book of abstracts 3 - Railway line capacity consumption of different railway signalling systems under scheduled and disturbed conditions Presenter: Dr. GOVERDE, Rob (Delft University of Technology) The characteristics of a signalling and automatic train protection (ATP) system have a significant impact on the capacity and stability of a railway line. The capacity consumption of a railway line can be calculated using the UIC timetable compression method for given infrastructure characteristics, rolling stock characteristics, and timetable pattern (UIC, 2004). This compression method is based on a deterministic microscopic calculation of conflict-free train paths with minimum headway times using blocking time theory (Hansen and Pachl, 2008). In addition, the UIC capacity method gives empirically derived guidelines on the total required buffer time in a timetable pattern to be stable for delays. However, this method does not consider the actual capacity consumption under disturbed conditions. In the presence of delays, train path conflicts occur depending on the scheduled buffer time between train paths. In practice this means that a train has to brake in response to the signalling system and possibly wait in rear of a stop signal. This leads to changed train trajectories with increased blocking times so that following trains may also be affected. The actual response to the signals depends on the specific signalling system and constraints of the ATP system, and can be quite different. In a standard three-aspect signalling system, trains have to brake from two signals in advance of the occupied block to a restricted speed and continue with this restricted speed until a final brake before a red signal. In contrast, a cab signalling system as ETCS allows a train to proceed until an approach indication point that is determined by a dynamically computed braking curve onboard. This braking curve depends on the actual train speed and braking characteristics as well as on the infrastructure description until the end of the movement authority (such as slopes). Also the time of re-acceleration after an improved
Load more

Recommended publications
  • An Algorithm Based on Semidefinite Programming for Finding Minimax
    Takustr. 7 Zuse Institute Berlin 14195 Berlin Germany BELMIRO P.M. DUARTE,GUILLAUME SAGNOL,WENG KEE WONG An algorithm based on Semidefinite Programming for finding minimax optimal designs ZIB Report 18-01 (December 2017) Zuse Institute Berlin Takustr. 7 14195 Berlin Germany Telephone: +49 30-84185-0 Telefax: +49 30-84185-125 E-mail: [email protected] URL: http://www.zib.de ZIB-Report (Print) ISSN 1438-0064 ZIB-Report (Internet) ISSN 2192-7782 An algorithm based on Semidefinite Programming for finding minimax optimal designs Belmiro P.M. Duarte a,b, Guillaume Sagnolc, Weng Kee Wongd aPolytechnic Institute of Coimbra, ISEC, Department of Chemical and Biological Engineering, Portugal. bCIEPQPF, Department of Chemical Engineering, University of Coimbra, Portugal. cTechnische Universität Berlin, Institut für Mathematik, Germany. dDepartment of Biostatistics, Fielding School of Public Health, UCLA, U.S.A. Abstract An algorithm based on a delayed constraint generation method for solving semi- infinite programs for constructing minimax optimal designs for nonlinear models is proposed. The outer optimization level of the minimax optimization problem is solved using a semidefinite programming based approach that requires the de- sign space be discretized. A nonlinear programming solver is then used to solve the inner program to determine the combination of the parameters that yields the worst-case value of the design criterion. The proposed algorithm is applied to find minimax optimal designs for the logistic model, the flexible 4-parameter Hill homoscedastic model and the general nth order consecutive reaction model, and shows that it (i) produces designs that compare well with minimax D−optimal de- signs obtained from semi-infinite programming method in the literature; (ii) can be applied to semidefinite representable optimality criteria, that include the com- mon A−; E−; G−; I− and D-optimality criteria; (iii) can tackle design problems with arbitrary linear constraints on the weights; and (iv) is fast and relatively easy to use.
    [Show full text]
  • E-News N21 Coul.Qxp
    The electronic newsletter of the International Union of Railways n°21 - 7th September 2006 Proximity with UIC members Latest news FS: Innocenzo Cipolletta appointed President, Mauro Moretti new Chief Executive Officer Mr. Innocenzo Cipolletta, an Economist, who has been during 10 years Director General of the Italian confederation Confindustria, is appointed as the new President of FS Group. Mr. Mauro Moretti, who was previously the Amminstratore Delegato (CEO) of Rete Ferroviaria Italiana (RFI), the Italian railway infrastructure manager -and currently President of the UIC Infrastructure Forum at international level- is appointed as the new Amministratore Delegato Innocenzo Cipolletta Mauro Moretti (CEO) of the Italian railways FS Group. They are succeeding Elio Catania who is leaving the Italian Railways Group. UIC conveys its sincere congratulations to Mr. Cipolletta and Mr. Moretti for theses appoint- ments and many thanks to Mr. Elio Catania for his action in UIC. Information session for representatives from Russian railways at UIC HQ A group of 25 representati- ves from Russian railways participating to a study trip in France visited the UIC Headquarters in Paris on Monday 28th August. Members of this delegation were general directors, senior managers and engi- 1 neers from the Russian rail- L L L way companies and a series of rail- way organisations. The represented in particular JSC Russian Railways (RZD), October Railways (Saint- Petersburg), Oural SA, VNIIAS (Ministère), and cooperating compa- nies as Radioavionika, etc. This information session on UIC role and activities was opened by UIC Chief Executive Luc Aliadière. By wel- coming the delegation, Luc Aliadière underlined the promising perspectives resulting from Russian railways' mem- bership in UIC and from the enhanced cooperation between RZD and UIC in a series of strategic cooperation issues: development of Euro-Asian corridors, partnership in business, technology and research, training, etc.
    [Show full text]
  • Solving Mixed Integer Linear and Nonlinear Problems Using the SCIP Optimization Suite
    Takustraße 7 Konrad-Zuse-Zentrum D-14195 Berlin-Dahlem fur¨ Informationstechnik Berlin Germany TIMO BERTHOLD GERALD GAMRATH AMBROS M. GLEIXNER STEFAN HEINZ THORSTEN KOCH YUJI SHINANO Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite Supported by the DFG Research Center MATHEON Mathematics for key technologies in Berlin. ZIB-Report 12-27 (July 2012) Herausgegeben vom Konrad-Zuse-Zentrum f¨urInformationstechnik Berlin Takustraße 7 D-14195 Berlin-Dahlem Telefon: 030-84185-0 Telefax: 030-84185-125 e-mail: [email protected] URL: http://www.zib.de ZIB-Report (Print) ISSN 1438-0064 ZIB-Report (Internet) ISSN 2192-7782 Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite∗ Timo Berthold Gerald Gamrath Ambros M. Gleixner Stefan Heinz Thorsten Koch Yuji Shinano Zuse Institute Berlin, Takustr. 7, 14195 Berlin, Germany, fberthold,gamrath,gleixner,heinz,koch,[email protected] July 31, 2012 Abstract This paper introduces the SCIP Optimization Suite and discusses the ca- pabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming frame- work SCIP. We explain how these can be used in concert to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, give an overview of available interfaces, and outline plans for future development. ∗A Japanese translation of this paper will be published in the Proceedings of the 24th RAMP Symposium held at Tohoku University, Miyagi, Japan, 27{28 September 2012, see http://orsj.or.
    [Show full text]
  • Linear Underestimators for Bivariate Functions with a Fixed Convexity Behavior
    Takustraße 7 Konrad-Zuse-Zentrum D-14195 Berlin-Dahlem fur¨ Informationstechnik Berlin Germany MARTIN BALLERSTEINy AND DENNIS MICHAELSz AND STEFAN VIGERSKE Linear Underestimators for bivariate functions with a fixed convexity behavior This work is part of the Collaborative Research Centre “Integrated Chemical Processes in Liquid Multiphase Systems” (CRC/Transregio 63 “InPROMPT”) funded by the German Research Foundation (DFG). Main parts of this work has been finished while the second author was at the Institute for Operations Research at ETH Zurich and financially supported by DFG through CRC/Transregio 63. The first and second author thank the DFG for its financial support. Thethirdauthor was supported by the DFG Research Center MATHEON Mathematics for key technologies and the Research Campus MODAL Mathematical Optimization and Data Analysis Laboratories in Berlin. y Eidgenossische¨ Technische, Hochschule Zurich,¨ Institut fur¨ Operations Research, Ramistrasse¨ 101, 8092 Zurich (Switzerland) z Technische Universitat¨ Dortmund, Fakultat¨ fur¨ Mathematik, M/518, Vogelpothsweg 87, 44227 Dortmund (Germany) ZIB-Report 13-02 (revised) (February 2015) Herausgegeben vom Konrad-Zuse-Zentrum fur¨ Informationstechnik Berlin Takustraße 7 D-14195 Berlin-Dahlem Telefon: 030-84185-0 Telefax: 030-84185-125 e-mail: [email protected] URL: http://www.zib.de ZIB-Report (Print) ISSN 1438-0064 ZIB-Report (Internet) ISSN 2192-7782 Technical Report Linear Underestimators for bivariate functions with a fixed convexity behavior∗ A documentation for the SCIP constraint handler cons bivariate Martin Ballersteiny Dennis Michaelsz Stefan Vigerskex February 23, 2015 y Eidgenossische¨ Technische Hochschule Zurich¨ Institut fur¨ Operations Research Ramistrasse¨ 101, 8092 Zurich (Switzerland) z Technische Universitat¨ Dortmund Fakultat¨ fur¨ Mathematik, M/518 Vogelpothsweg 87, 44227 Dortmund (Germany) x Zuse Institute Berlin Takustr.
    [Show full text]
  • Nonlinear Programming Techniques for Operative Planning in Large Drinking Water Networks Jens Burgschweiger1, Bernd Gnädig2 and Marc C
    14 The Open Applied Mathematics Journal, 2009, 3, 14-28 Open Access Nonlinear Programming Techniques for Operative Planning in Large Drinking Water Networks Jens Burgschweiger1, Bernd Gnädig2 and Marc C. Steinbach3,* 1Berliner Wasserbetriebe, Abt. NA-G/W, 10864 Berlin, Germany 2Düsseldorf, Germany 3Leibniz Universität Hannover, IfAM, Welfengarten 1, 30167 Hannover, Germany Abstract: Mathematical decision support for operative planning in water supply systems is highly desirable; it leads, however, to very difficult optimization problems. We propose a nonlinear programming approach that yields practically satisfactory operating schedules in acceptable computing time even for large networks. Based on a carefully designed model supporting gradient-based optimization algorithms, this approach employs a special initialization strategy for convergence acceleration, special minimum up and down time constraints together with pump aggregation to handle switching decisions, and several network reduction techniques for further speed-up. Results for selected application scenarios at Berliner Wasserbetriebe demonstrate the success of the approach. Keywords: Water supply, large-scale nonlinear programming, convergence acceleration, discrete decisions, network reduction. INTRODUCTION • experiments with various optimization models and methods [36, 37], Stringent requirements on cost effectiveness and environmental compatibility generate an increased demand • a first nonlinear programming (NLP) model for model-based decision support tools for designing and developed under GAMS [38], operating municipal water supply systems. This paper deals • numerical results for a substantially reduced with the minimum cost operation of drinking water network graph using (under GAMS) the SQP codes networks. Operative planning in water networks is difficult: CONOPT, SNOPT, and the augmented Lagrangian a sound mathematical model leads to nonlinear mixed- code MINOS.
    [Show full text]
  • 54 OP08 Abstracts
    54 OP08 Abstracts CP1 Dept. of Mathematics Improving Ultimate Convergence of An Aug- [email protected] mented Lagrangian Method Optimization methods that employ the classical Powell- CP1 Hestenes-Rockafellar Augmented Lagrangian are useful A Second-Derivative SQP Method for Noncon- tools for solving Nonlinear Programming problems. Their vex Optimization Problems with Inequality Con- reputation decreased in the last ten years due to the com- straints parative success of Interior-Point Newtonian algorithms, which are asymptotically faster. In the present research We consider a second-derivative 1 sequential quadratic a combination of both approaches is evaluated. The idea programming trust-region method for large-scale nonlin- is to produce a competitive method, being more robust ear non-convex optimization problems with inequality con- and efficient than its ”pure” counterparts for critical prob- straints. Trial steps are composed of two components; a lems. Moreover, an additional hybrid algorithm is defined, Cauchy globalization step and an SQP correction step. A in which the Interior Point method is replaced by the New- single linear artificial constraint is incorporated that en- tonian resolution of a KKT system identified by the Aug- sures non-accent in the SQP correction step, thus ”guiding” mented Lagrangian algorithm. the algorithm through areas of indefiniteness. A salient feature of our approach is feasibility of all subproblems. Ernesto G. Birgin IME-USP Daniel Robinson Department of Computer Science Oxford University [email protected]
    [Show full text]
  • Using SCIP to Solve Your Favorite Integer Optimization Problem
    Using SCIP to Solve Your Favorite Integer Optimization Problem Gregor Hendel, [email protected], www.zib.de/hendel Monash University, Melbourne March 12, 2019 Gregor Hendel{ Using SCIP 1/78 Zuse Institute Berlin { Fast Algorithms, Fast Computers A research institute and computing center of the State of Berlin with research units: • Numerical Analysis and Modeling • Visualization and Data Analysis • Optimization: Energy { Transportation { Health { Mathematical Optimization Methods • Scientific Information Systems • Computer Science and High Performance Computing Gregor Hendel{ Using SCIP 2/78 What is SCIP? SCIP (Solving Constraint Integer Programs) . • provides a full-scale MIP and MINLP solver, • is constraint based, • incorporates • MIP features (cutting planes, LP relaxation), and • MINLP features (spatial branch-and-bound, OBBT) • CP features (domain propagation), • SAT-solving features (conflict analysis, restarts), • is a branch-cut-and-price framework, • has a modular structure via plugins, • is free for academic purposes, • and is available in source-code under http://scip.zib.de ! Gregor Hendel{ Using SCIP 3/78 Meet the SCIP Team 31 active developers • 7 running Bachelor and Master projects • 16 running PhD projects • 8 postdocs and professors 4 development centers in Germany • ZIB: SCIP, SoPlex, UG, ZIMPL • TU Darmstadt: SCIP and SCIP-SDP • FAU Erlangen-N¨urnberg: SCIP • RWTH Aachen: GCG Many international contributors and users • more than 10 000 downloads per year from 100+ countries Careers • 10 awards for Masters and PhD theses:
    [Show full text]
  • The SCIP Optimization Suite
    The SCIP Optimization Suite Gerald Gamrath Zuse Institute Berlin EWO Seminar February 13, 2015 Gerald Gamrath (ZIB): The SCIP Optimization Suite 1 ZIB: Fast Algorithms – Fast Computers Konrad-Zuse-Zentrum für Informationstechnik Berlin I non-university research institute and computing center of the state of Berlin I Research Units: I numerical analysis and modeling I visualization and data analysis I optimization: energy–traffic–telecommunication–linear and nonlinear IP I scientific information systems I distributed algorithms and supercomputing I President: Martin Grötschel I more information: http://www.zib.de Gerald Gamrath (ZIB): The SCIP Optimization Suite 2 ZIB: Fast Algorithms – Fast Computers Konrad-Zuse-Zentrum für Informationstechnik Berlin I non-university research institute and computing center of the state of Berlin I Research Units: I numerical analysis and modeling I visualization and data analysis I optimization: energy–traffic–telecommunication–linear and nonlinear IP I scientific information systems I distributed algorithms and supercomputing I President: Martin Grötschel I more information: http://www.zib.de Gerald Gamrath (ZIB): The SCIP Optimization Suite 2 Outline SCIP –SolvingConstraintIntegerPrograms Constraint Integer Programming Solving Constraint Integer Programs History and Applications http://scip.zib.de Gerald Gamrath (ZIB): The SCIP Optimization Suite 3 What is a Constraint Integer Program? Mixed Integer Program Constraint Program Objective function: Objective function: . linear function . arbitrary function Feasible set: Feasible set: . described by linear constraints . given by arbitrary constraints Variable domains: Variable domains: . real or integer values . arbitrary (usually finite) min cT x min c(x) s.t. Ax ≤ b s.t. x ∈ F I C I (xI , xC ) ∈ Z × R (xI , xN ) ∈ Z × X Gerald Gamrath (ZIB): The SCIP Optimization Suite 4 What is a Constraint Integer Program? Constraint Integer Program Objective function: .
    [Show full text]
  • Computational Aspects of Infeasibility Analysis in Mixed Integer Programming
    Takustr. 7 Zuse Institute Berlin 14195 Berlin Germany JAKOB WITZIG TIMO BERTHOLD STEFAN HEINZ Computational Aspects of Infeasibility Analysis in Mixed Integer Programming ZIB Report 19-54 (November 2019) Zuse Institute Berlin Takustr. 7 14195 Berlin Germany Telephone: +49 30-84185-0 Telefax: +49 30-84185-125 E-mail: [email protected] URL: http://www.zib.de ZIB-Report (Print) ISSN 1438-0064 ZIB-Report (Internet) ISSN 2192-7782 Computational Aspects of Infeasibility Analysis in Mixed Integer Programming Jakob Witzig,1 Timo Berthold,2 and Stefan Heinz3 1Zuse Institute Berlin, Takustr. 7, 14195 Berlin, Germany [email protected] 2Fair Isaac Germany GmbH, Stubenwald-Allee 19, 64625 Bensheim, Germany [email protected] 3Gurobi GmbH, Ulmenstr. 37–39, 60325 Frankfurt am Main, Germany [email protected] November 6, 2019 Abstract The analysis of infeasible subproblems plays an important role in solv- ing mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to gener- ate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications, obtained by domain propagation, that led to infeasibility. The result of this analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept is called conflict graph analysis and has its origin in solving satisfiability problems and is similarly used in con- straint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. Every ray of the dual LP provides a set of multipliers that can be used to generate a single new globally valid linear constraint.
    [Show full text]
  • Classical Benders Decomposition (KC203) Cluster: CPAIOR Chair: Jean-François Cordeau, HEC Montreal
    Sunday, May 29, 2016 9:00am - 10:00am Session: Classical Benders Decomposition (KC203) Cluster: CPAIOR Chair: Jean-François Cordeau, HEC Montreal Classical Benders Decomposition Jean-François Cordeau, HEC Montréal, [email protected] Benders decomposition is a mathematical decomposition technique designed to solve large- scale linear and mixed-integer programs comprising two sets of variables such that a more tractable subproblem is obtained when the values of some "complicating" variables are fixed. The technique works by projecting the original problem on the space of the complicating variables, and by using a cutting plane method where cuts are generated by solving the subproblem. The purpose of this masterclass is to introduce the basic Benders decomposition methodology, to present several computational refinements that have shown to improve performance, and to discuss some recent developments. ______________________________________________________________________________ 10:15am - 11:15am Session: Logic-Based Benders Decomposition (KC203) Cluster: CPAIOR Chair: John Hooker, Carnegie Mellon University Logic-Based Benders Decomposition John Hooker, Carnegie Mellon University, [email protected] This is a tutorial on logic-based Benders decomposition, which generalizes the classical Benders method so as to accommodate an arbitrary subproblem rather than only a linear or continuous nonlinear programming problem. This allows one to apply Benders profitably to any problem that simplifies or decouples when certain variables are
    [Show full text]
  • Railcorp Annual Report 2019-20 Volume 1
    RailCorp Annual Report Volume 1 • 2019–20 RailCorp 20-44 Ennis Road Milsons Point NSW 2061 Contact us at: [email protected] This Annual Report was produced wholly by Annual Report 2019–20 Annual Report RailCorp. This Annual Report can be accessed on the Transport for NSW website transport.nsw.gov.au ISBN: 978-1-63684-453-4 © 2020 RailCorp Unless otherwise stated, all images (including photography, background images, icons and illustrations) are the property of RailCorp. Users are welcome to copy, reproduce and distribute the information contained in this report for non-commercial purposes only, provided ii acknowledgement is given to RailCorp as the source. RailCorp Letter to the Minister The Hon. Andrew Constance MP Minister for Transport and Roads Parliament House Macquarie Street Sydney NSW 2000 Dear Minister, It is our pleasure to provide the Rail Corporation New South Wales (RailCorp) Annual Report for the financial year, 1 July 2019 to 30 June 2020, for your information and presentation to Parliament. This report has been prepared in accordance with the Annual Report (Statutory Bodies) Act 1984, the Annual Reports (Statutory Bodies) Regulation 2015 and the Public Finance and Audit Act 1983. Yours sincerely Bruce Morgan Anne McDonald Chair Director 20 November 2020 Letter of submission • iii Foreword 2 From the Chief Executive 4 Overview 6 About RailCorp 8 Annual Report 2019–20 Annual Report Financial performance 9 Appendices 12 Contents Appendix 1: Changes in Acts and subordinate legislation from 1 July 2019 to 30 June 2020
    [Show full text]
  • ORR Best Practice Study Visit to Australia
    ORR Best Practice Study Visit to Australia - 20 August to 05 September 2007 David Brace and Paul Dawkins (CDL Group) page 1 Contents Page No Executive Summary 4 1. Purpose 7 2. Introduction 8 3. Background 9 4. Issues 10 5. Funding and Financial Regulation 11 6. Findings 13 7. Safety and other Regulators 20 8. Other Meetings and Visits 24 Appendices A Meetings and Visits Schedule 29 B Papers Provided by Hosts 36 C Responses to Standard Set of Questions 38 } 2 Glossary of Acronyms ACCC The Australian Competition and Consumer Commission ARA Australasian Railway Association ARTC Australian Rail Track Corporation ATSB Australian Transport Safety Bureau BHP BHP Billiton World's largest resource company CASA Civil Aviation Safety Authority COMET Consortium of Metropolitan Transport Operators CPI Consumer Price Index CRC Co-operative Research Centre DoI Department of Infrastructure, Victoria DORC Depreciated Optimised Replacement Cost gmpta gross million tonnes per annum ICE Institution of Civil Engineers IPART Independent Pricing and Regulatory Tribunal ISG Infrastructure Services Group (Queensland Rail) ITSRR Independent Transport Safety and Reliability Regulator OTSI Office of Transport Safety Investigation PDFH Passenger Demand Forecasting Handbook PLC Programme Logic Controller PPP Public Private Partnership QCA Queensland Competition Authority QRNA Queensland Rail Network Access QR Queensland Rail QT Queensland Transport RailBAMS Acoustic Bearing Monitor SCT Specialised Container Transport TIDC Transport Infrastructure Development Corporation TSC Transport Services Contract WILD Wheel Impact Loading Device Doc # 285015.013 Executive Summary The visit to Australia between 22 August and 04 September was arranged around 6½ full days of meetings, 1½ days of site visits and a full day asset management workshop.
    [Show full text]