FYP Progress Presentation

Genetic Algorithm

(GA)

Presented By:

Oluwaseun Akintimehin

Project Goals

Develop / apply a GA search algorithm to a basic timetable scenario.

Visually display results and incorporate low level user interface.

Define full New Engineering Building (NEB) timetabling model and fitness criteria.

Test a range of scenarios and verify correctness. Define limitations of the system.

Develop / apply a GA search algorithm to a basic timetable scenario.

Develop a series of diagrams illustrating each project phase.

Define a basic timetabling problem. Develop a solution to the timetabling problem. Apply GA search algorithm to the timetabling

solution.

Illustration of Project Phase

A Basic Timetabling Problem

A program is asked to read the following input data, and to generate a suitable fitness without taking into account the GA process.

• Number of Modules: 8• Number of Staffs: 8• Number of Groups: 2• Number of Room: 3• Number of Periods: 12(4 for each room)• Number of Days: 1

Rules

1 1 1 2

2 3 2 1

3 1 3 2

4 2 4 2

5 2 5 2

6 3 6 1

7 3 7 1

8 3 8 1

GroupModule Staff Nos. Hours

Limits

• A staff can not give more than one lecture at the same time period.• Teaching group can not learn more subjects at the same time period.• Room can be devoted to only one module in the same time.• Module can not be assigned time period different from the times stated.• Group and staff should be assigned to the right module based on the rules.

Solution For Timetabling Problem

• Initialise variables according to problem definition.Mmax = 8 //Max value of ModulesGmax = 2 //Max value of GroupsSmax = 8 //Max value of StaffsRmax = 3 //Max value of RoomsTmax = 4 //Max value of Time periodsF = Fitness

for(r=1 to r=Rmax){ for(t=1 to t=tmax) {

cell[r,t,m] = RandomNumb(1 to Mmax)cell[r,t,g] = RandomNumb(1 to Gmax)cell[r,t,s] = RandomNumb(1 to Smax)

}}

Module is represented as 1 in three dimensional arrayGroup is represented as 2 in three dimensional arrayStaff is represented as 3 in three dimensional array

E.g. cell[1,1,1] represents the value of m where r =1and t =1. cell[3,2,3] represents the value of s where r = 3 and t = 2.

Rules

Modules Groups Staff Nos. Hours1 1 1 2

2 3 2 1

3 1 3 2

4 2 4 2

5 2 5 2

6 3 6 1

7 3 7 1

8 3 8 1

cell(ref)[m,g] allows the checking the group with respect to the module.cell(ref)[m,s] allows the checking the staff with respect to the module.nh(ref)[m] allows the checking of the number of hours assigned to the module.

• Run first test to see that the right module, group and staff are assigned according to the problem definition. Increment fitness as applicable.

for(r=1 to r=Rmax){ for(t=1 to t=Tmax { F = 2 (default) cell[r,t,1] = m if(cell[r,t,2] |= cell(ref) [m,g]

tempFit = 1 if(cell[r,t,3] |= cell(ref)[m,3]

tempFit = 1else

tempFit = 0}F = F + tempFit

}

• Run second test to make sure the modules are assigned the right number of hours. Increment or decrement fitness according the difference in error.

for(r=1 to r=Rmax){ for(t=1 to t=Tmax) {

Diff = | Nh[r,t,m] – Nh(ref)[m] |tempFit = Diff

Fit = Fit + tempFit }

F = F + Fit}

• Run test to prevent group and staff clashes between time periods.

for(t=1 to t=Tmax){ for(r=1 to r=Rmax) { for(s=r+1 to s=Rmax) {

if(cell[r,t,2] = cell[s, t, 2]tempFit++F=tempFit

} } }The same code will be used for testing the staff (cell[r,t,3]).

The following are different scenarios of the timetable and their fitness.

Scenario 1

1, 1, 1 5, 2, 5 2, 3, 2

4, 2, 4 6, 3, 6 1, 1, 1

3, 1, 3 5, 2, 5 8, 3, 8

7, 3, 7 4, 2, 4 3, 1, 3

Fitness = 0Scenario 2

1, 1, 1 5, 3, 5 2, 3, 2

4, 2, 4 6, 3, 6 1, 1, 1

3, 1, 3 5, 2, 5 8, 1, 8

7, 2, 7 4, 2, 4 3, 1, 3 Fitness = 6

Scenario 4

1, 2, 2 5, 2, 3 2, 1, 2

4, 3, 1 6, 3, 2 1,2, 1

3, 3, 5 5, 1, 5 8, 3, 2

7, 1, 4 4, 3, 4 3, 2, 3

Fitness = 24

Project Objective Timeline

Goal Target Date Length of Time

Code Sample Design 1st February 2006 10 days

Develop / Apply GA 13th February 7 days

Define full NEB Design 23th February 7 days

Develop / Apply GA 1st March 13 days

Quality Testing / Research

15th March 7 days

Final Report 22nd March 10 days