Modeling and Optimization of Traffic Flow in Urban Areas - Czech ...

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40 Chapter 4 TORSCHE Scheduling Toolbox for Matlabedges are precedence constraints between these tasks. For simple schedulingproblems, the object Taskset can be directly created from a vector ofthe tasks processing times. In this case, the tasks are created automaticallyinside the object constructor. There are also other ways how to create aninstance of the set of tasks in order to simplify the user interface as much aspossible.Another class, Problem, is used for the classification of deterministicscheduling problems in Graham and B̷lażewicz notation [Blaz 83]. This notationconsists of three parts (α|β|γ). The first part describes the processorenvironment (e.g. number and type of processors), the second part describesthe task characteristics of the scheduling problem (e.g. precedence constrains,release time). The last part denotes the optimality criterion (e.g. schedulemakespan minimization). The following example shows the notation stringused as an input to the class constructor:prob = problem(’P|prec|Cmax’)This instance of the class Problem represents the scheduling problem onparallel identical processors where the tasks have precedence constraints andthe objective is to minimize the schedule makespan.All of the above mentioned classes are designed to be maximally effectivefor users and developers of scheduling algorithms. The toolbox includesdozens of scheduling algorithmsscheduling algorithm which are stored as Matlabfunctions with at least two input parameters and at least one outputparameter. The first input parameter has to be an instance of the Tasksetclass containing the tasks to be scheduled. The second one has to be an instanceof the Problem class describing the required scheduling problem. Theoutput parameter is an instance of the Taskset class containing the resultingschedule. A typical syntax of the scheduling algorithm call is:TSout = algorithmname(TS,problem[,processors[,parameters]])where:TSout is the instance of the Taskset with the resulting schedule,algorithmname is the algorithm name,TS is the instance of the Taskset to be scheduled,
4.2 Tool Architecture and Basic Notation 41problem is the instance of the Problem class,processors is the number of processors to be used,parameters denotes additional parameters, e.g. algorithm strategy, etc.The typical work-flow of scheduling problem solution is shown on an UMLInteraction Overview Diagram (see Fig. 4.3). There are several sequencediagrams (sd) used. The first two “Create Taskset 1” and “Create Taskset 2”show the constitution of a Taskset instance by both of the above describedways. The third one, called “Classification”, shows the constitution of aProblem instance. The following sequence diagram “Scheduling” presentsthe call of the scheduling algorithm. The scheduling algorithm is describedseparately in the “Scheduling Algorithm” diagram, which is divided into threeparts. The first one is checking of the input parameters (“Read Properties”).The second one is constituted by the solver of a scheduling algorithm andthe final part stores the resulting schedule into the instance of the Taskset(“Schedule to the Tasks”). The last diagram “Gantt Chart” presents thefinal schedule conversion to a Gantt chart, i.e. the graphical representationof a schedule.Furthermore, the toolbox contains objects to handle problems like openshop, flow shop and job shop, it also supports limited buffers and transportrobots. For more details please see the toolbox documentation [Kuti 07].4.2.2 Graph PartA lot of scheduling problems can be solved with the assistance of the graphtheory. Therefore, the second part of the toolbox is aimed at graph theoryalgorithms. All algorithms are available as a method of the main class Graphwhich is used to describe the directed graph.There are several different ways to create an instance of the class Graph.The graph is generally described by an adjacency matrix. In this case, theGraph object is created by the command with the following syntax:G = graph(’adj’,A)where the variable A is an adjacency matrix. Similarly, it is possible to createthe Graph by an incidence matrix. Another way how to create the Graphobject is based on a matrix of edge weights.
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Czech Technical University in Pragu
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This thesis is dedicated to my wife
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Nomenclatureα|β|γ Graham and B̷
Page 7 and 8: NomenclatureviiR 0+ set of non-nega
Page 9 and 10: AbbreviationsCCPN Constant speed Co
Page 11 and 12: Goals and ObjectivesThis thesis wil
Page 13 and 14: ContentsGoals and Objectivesxi1 Int
Page 17 and 18: List of Tables2.1 Traffic data for
Page 19 and 20: Chapter 1IntroductionThe urban traf
Page 21 and 22: 1.1 Related Work 3Traffic stream mo
Page 23 and 24: Chapter 2Simple Light ControledInte
Page 25 and 26: 2.2 Extended Queue Model 72 E( k)AB
Page 27 and 28: 2.2 Extended Queue Model 9E [s]4000
Page 29 and 30: 2.4 Control of The Simple Intersect
Page 37 and 38: Chapter 3General Light ControlledIn
Page 39 and 40: 3.2 Continuous Petri Net 21take the
Page 41 and 42: 3.2 Continuous Petri Net 23v 5V 5vD
Page 43 and 44: 3.3 Light Controlled Intersection M
Page 49 and 50: 3.4 Performance Evaluation 31-1V[uv
Page 51 and 52: 3.4 Performance Evaluation 33-1V [u
Page 53 and 54: Chapter 4TORSCHE SchedulingToolbox
Page 55 and 56: 4.2 Tool Architecture and Basic Not
Page 57: 4.2 Tool Architecture and Basic Not
Page 61 and 62: 4.2 Tool Architecture and Basic Not
Page 63 and 64: 4.3 Implemented Algorithm 45tasks a
Page 65 and 66: 4.3 Implemented Algorithm 47leg 1p=
Page 67 and 68: 4.3 Implemented Algorithm 49unit j
Page 69 and 70: 4.3 Implemented Algorithm 51P 2P 1
Page 71 and 72: Chapter 5Traffic Flow OptimizationT
Page 73 and 74: 5.2 Traffic Region Model 5514 1516
Page 75 and 76: 5.3 Tasks Definition for Intersecti
Page 77 and 78: 5.4 Scheduling with Communication D
Page 79: 5.5 Summary 61Intersection 6T 2,6T
Page 82 and 83: 64 Chapter 6 Conclusionsoptimal und
Page 85 and 86: Appendix ATORSCHE AlgorithmsA.1 Sch
Page 87 and 88: Bibliography[Abou 09] K. Aboudolas,
Page 89 and 90: Bibliography 71[Febb 06] A. D. Febb
Page 91 and 92: Bibliography 73[Kwak 72]Cybernetics
Page 93: Bibliography 75[Tolb 01] C. Tolba.
Page 96 and 97: 78 Indexphase, 3offset, 3, 53split,
Page 99 and 100: List of Author’s PublicationsPape
Page 101: List of Author’s Publications 83P
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