a multi-objective bisexual reproduction genetic algorithm for ...

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These results show that all constraints presented in section 1.3 have been
satisfied. Every “course + section” is scheduled exactly once in a week. No course is
scheduled cross morning and afternoon working sessions. Neither a class nor a
lecturer nor a classroom is assigned to more than one course at the same time. For
example, shown in Table 4-3, section 001 of course ENL308 is scheduled for lecturer
00003 using classroom B201A03 on day 4 (Friday) and in the time-slots: 0, 1, and 2.
Therefore, this lecturer and this classroom are not booked for other courses at this
time.
Once a class of students studies from a list of courses, these courses have to be
scheduled to different time periods. For example, shown in Table 4-1, class BSCS05B
studies section 001 of courses: CSC215, CSC221, CSC210, and CSC211, and section
002 of courses: ECE217, ECE218, and MAT220. Therefore these “course + section”
are scheduled to different time periods. Another example is shown in Table 4-3.
Section 001 of course ENL307 is attended by both classes: BSCS04A and BSCS04B.
Therefore, this course section is scheduled to the same time periods and the same
classroom so that these classes can attend it as well as their other courses.
Other constraints presented in section 1.3 have also been satisfied, but they are
not introduced here.
The decentralized course scheduling program must give results that do not
conflict with the centralized course scheduling output. If a class is scheduled by the
centralized course scheduling program, then the decentralized course scheduling
program has to schedule the remaining courses that concern this class to another time.
For example, shown in Table 4-3, the centralized course scheduling program
scheduled the courses that are attended by class BSEE06A. Therefore, the
decentralized course scheduling program scheduled other courses studied by this class
to another time, shown in Table 4-4.