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3 The GA is based on the principle of survival of the fittest members of the population to produce the solution. The selected individual according to the fitness level of the problem domain creates the set of solutions. The GA is an iterative process that is repeated until the convergence criterion is satisfied. Grid computing, most simply stated, is distributed computing. The goal is to create the illusion of a simple yet large and powerful self-managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources [7]. Not all applications are suitable for the use of the grid computing. We need to look at considerations for an application to run in a grid environment where resources are dynamically allocated based on actual needs. Normally, an application consists of jobs that can be executed in parallel, serial, and networked. If an application consists of several jobs that can be executed in parallel, a grid may be very suitable for effective execution on dedicated nodes, especially in the case when there is no or a very limited exchange of data among the jobs [8]. 1.2 The Objectives of the Study The objectives of this study can be defined as follows: 1.2.1 To provide a system that helps multiple faculty universities solve their course scheduling problems. 1.2.2 To investigate the use of the proposed GA and the grid computing environment to the course scheduling problem in multiple faculty universities. 1.3 The Scope of the Study The scope of this study can be defined as follows: 1.3.1 The system must satisfy the following hard constraints: 1.3.1.1 Every course must be scheduled exactly once in a week. 1.3.1.2 For courses at each faculty, values assigned to days in a week are Monday, Tuesday, Wednesday, Thursday, and Friday. In addition, 8 time-slots is used in a day. Hours are assigned to time-slots are 08:00-12:00 and 13:00-17:00. No course is scheduled cross morning and afternoon working sessions. Figure 1-3 presents a sample timetable for a classroom.
4 Classroom i Time-slot Hour Mon Tue Wed Thu Fri 0 08:00-09:00 Course 1 Course 3 Course 15 1 09:00-10:00 Course 1 Course 4 Course 3 Course 15 2 10:00-11:00 Course 1 Course 4 Course 2 Course 15 3 11:00-12:00 Course 2 Course 15 4 13:00-14:00 Course 8 Course 5 Course 6 Course 7 5 14:00-15:00 Course 8 Course 5 Course 6 Course 7 6 15:00-16:00 Course 13 Course 5 Course 19 Course 7 7 16:00-17:00 Course 13 Course 19 Course 7 FIGURE 1-3 Sample timetable for a classroom 1.3.1.3 Neither a class nor a lecturer nor a classroom is assigned to more than one course at the same time. 1.3.1.4 Each course must be booked to a classroom that is large enough to hold students of that course. 1.3.1.5 In each semester, each class of students studies from list of courses in the curriculum. All these courses have to be scheduled to different times in each week so that all students in that class can attend. 1.3.1.6 If a course is attended by students who come from different classes, it has to be scheduled so that these students can attended this course and their other courses without any time conflicts. 1.3.1.7 Each lecturer can teach courses in his/her faculty and other faculties. 1.3.1.8 Lecturers can require some unavoidable working-sessions in a week. For instance, Dr. Tim cannot teach on Monday morning because of a weekly meeting. Therefore, his courses must be scheduled at another time. 1.3.1.9 Each course must be booked to a classroom of a designated classroom group. 1.3.2 The system tries to satisfy as much as possible the following soft constraint: The system avoids booking lecturers’ courses to their undesired time.
Page 1 and 2: COURSE SCHEDULING IN MULTIPLE FACUL
Page 3 and 4: ชื่อ : นายฮูเ
Page 5 and 6: TABLE OF CONTENTS Page Abstract (in
Page 7 and 8: LIST OF TABLES Table Page 2-1 Cours
Page 9 and 10: LIST OF FIGURES (CONTINUED) Figure
Page 11: 2 The classrooms are sometime share
Page 15 and 16: CHAPTER 2 LITERATURE REVIEW In this
Page 17 and 18: 9 teach effectively. However, in so
Page 19 and 20: 11 The set of vertexes are consider
Page 21 and 22: 13 Gueret et al. have implemented a
Page 23 and 24: 15 When the atoms are at a high tem
Page 25 and 26: 17 The outline of the basic genetic
Page 27 and 28: 19 As shown in Figure 2-6, first of
Page 29 and 30: 21 2.3.2.1 Crossover After we have
Page 31 and 32: 23 these chromosomes. According to
Page 33 and 34: 25 2.4.1 Application Considerations
Page 35 and 36: 27 Southern California, the Argonne
Page 37 and 38: 29 2.4.3.2 Application Programming
Page 39 and 40: 31 2.5 Summary The course schedulin
Page 41 and 42: 34 3.1.5 Phase 5: Measurement a) To
Page 43 and 44: 36 All the above problems can be pr
Page 45 and 46: 38 Client at a faculty Client at th
Page 47 and 48: 40 The Grid system is only used by
Page 49 and 50: 42 3.6 The Proposed Genetic Algorit
Page 51 and 52: 44 Chromosome x i Fitness = f(x i )
Page 53 and 54: 46 A population is a list of n chro
Page 55 and 56: 48 Lecturers register their busy ti
Page 57 and 58: 50 A course is booked to the time-l
Page 59 and 60: 52 As mentioned in the previous sec
Page 61 and 62: 54 GIIS from the client machine m1.
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56 The complete source code for man
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58 3.8.2.2 Stage 2 After the centra
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60 3.8.3.3 The Gatekeeper The gatek
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62 TABLE 4-1 (CONTINUED) Class Seme
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64 26 lecturers are assigned to tea
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66 TABLE 4-2 (CONTINUED) Course Sec
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68 This result shows that the GA ra
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70 should revise the chromosome rep
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72 - Population size : 10 - Crossov
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74 for network communication is muc
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76 TABLE 4-5 Timetable created by t
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CHAPTER 5 CONCLUSION 5.1 Conclusion
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REFERENCES 1. Alkan, A. and Ozcan,
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83 20. Burke, E. K. and Newall, J.
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85 38. Globus Toolkit [Online]. Ava
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88 This section presents the struct
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90 A.5 Building TABLE A-5 Building
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92 A.10 Program TABLE A-10 Program
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94 A.14 Timetable TABLE A-14 Timeta
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96 This section presents in detail
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98 TABLE B-2 Group, user ID and pas
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100 broadcastdelay 0.008 authentica
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102 mycapw [enter] During the above
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104 service gsigatekeeper { socket_
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106 B.3.3 Starting the MDS on All o
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108 B.4 Checking the Installation T
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110 This section introduces the ste
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112 C.3.2 Configuration This sectio
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114 [root@m1 root]#grid-proxy-info
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116 The system will automatically p
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118 C.6 Installing JDBC Driver on L
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120 This section presents how to co
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122 All the following files are com
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124 } } } try { ctx.close(); } catc
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126 }//for }else if(attribute.equal
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128 public static void main(String
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130 System.out.println(CentralizedS
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132 gassJob[jobCount]=new GassJob(t
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134 /** * Init job out listeners fo
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136 // Start GASS server if (! star
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138 // waits for DONE or FAILED sta
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140 //get RSL of Job having index i
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142 class Job { private String jobn
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145 BIOGRAPHY Name : Mr. Nguyen Con
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