For this program you will use simulated annealing to solve a small example of a real-world problem.
(you will have 29 hours to complete the assignment)
Consider the problem of producing a university class schedule. Each course must be taught. It must have a room, and a time. Only one course can be taught in a room at a time. The room must be able to hold the expected number of students. It must have an instructor. Each instructor can teach any of several courses, but only those courses, and there is an upper limit on how many courses one instructor can teach. A course can be taught by an adjunct or graduate student (‘Staff’), but faculty are preferred for teaching. Finally, we may have additional preferences regarding scheduling; for example, if there are courses that are usually taken the same semester, we would prefer (but not require) that they be taught in adjacent time slots, and if they’re in adjacent time slots, that they be in rooms that are close together. If a course has multiple sections, those sections should be separated in time; it doesn’t make sense to have a 1 PM section, then a 2 PM section of the same course.
You are given a list of 12 courses. (Some of these may be multiple sections of the same course, but that doesn’t affect our problem here.) You also have a list of several faculty members, and the courses each can teach. You also have a list of available rooms and time slots. Your task is to use simulated annealing to devise a suitable teaching schedule.
In a production system, we’d probably want the program to read the various options (courses, instructors, etc) from input files, but for this assignment you can use input files or put the data directly into your source code.
Courses and expected enrollments are: CS 101A (40), CS 101B (25), CS 201A (30), CS 201B (30), CS 191A (60), CS 191B (20), CS 291B (40), CS 291A (20), CS 303 (50), CS 341 (40), CS 449 (55), CS 461 (40).
Instructors and what they can teach:
- Hare: CS 101, CS 201, CS 291, CS 303, CS 449, CS 461
- Bingham: CS 101, CS 201, CS 191, CS 291, CS 449
- Kuhail: CS 303, CS 341
- Mitchell: CS 191, CS 291, CS 303, CS 341
- Rao: CS 291, CS 303, CS 341, CS 461
- Staff: any
Time slots: 10A, 11A, 12P, 1P, 2P, 3P, 4P (We’re assuming these are all MWF courses)
Rooms and capacities: Haag 301 (70), Haag 206 (30), Royall 204 (70), Katz 209 (50), Flarsheim 310 (80), Flarsheim 260 (25), Bloch 0009 (30)
Assign instructors, times, rooms, and courses. For your initial schedule, this will be random. Assess the fitness function as follows:
- For each course that is taught by an instructor who can teach it, other than Staff: +3
- For each course taught by Staff: +1
- For each course that is the only course scheduled in that room at that time: +5
- For each course that is in a room large enough to accommodate it: +5
- Room capacity is no more than twice the expected enrollment: +2
- For each course that does not have the same instructor teaching another course at the same time: +5
- For each schedule that has the same instructor teaching more than 4 courses: -5 per course over 4
- For each schedule that has Rao or Mitchell (graduate faculty) teaching more courses than Hare or Bingham (same number of courses is OK): -10
- CS 101 and CS 191 are usually taken the same semester; the same applies to CS 201 and CS 291. Therefore apply these rules to those pairs of courses:
- Courses are scheduled for same time: -15
- Courses are scheduled for adjacent times: +5
- if these courses are scheduled for adjacent times, and
- Are in the same building: +5 points
- Are both on the quad (Haag, Royall, Flarsheim): no modification
- 1 is in Katz and the other isn’t: -3
1 is in Bloch and the other isn’t: -3
(Yes, if one’s in Katz and the other’s in Bloch, that’s -6)
- CS101A and CS101B are scheduled 3 hours apart or more: +5
- CS191A and CS191B are scheduled 3 hours apart or more: +5
Annealing Schedule: It’s necessary to assign instructor, time, and room to each of 12 courses, so there are 36 items to be assigned. Lower your temperature parameter after 400 successful changes to the schedule, or 4000 attempts. Continue until you make a complete pass (4000 attempts) with no changes. Print your final schedule to an output file, along with its fitness score.
You may want to try running your program several times and see how much variation there is in the schedule or fitness score across multiple runs. Likewise, you may want to change your annealing schedule to reduce the temperature more slowly (T = 0.95T rather than T = 0.9T) and explore the relationship between running time and the fitness of the final schedule.
You will have to write it in C++ language.
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intro to artificial intelligence c was first posted on July 1, 2020 at 12:09 am.
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