def test_case13(self):
"""Testing the kPoint crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = kPoint(solution1,
solution2,
self.supervisors2,
self.students2,
k=15)
result = solution3.isValid(self.students2, self.supervisors2)
self.assertTrue(result)
def test_case6(self):
"""Testing the K Point Crossover function - for random 3sup:4stu solution"""
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution3 = kPoint(solution1,
solution2,
self.supervisors,
self.students,
k=3)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case1(self):
"""Testing the create random solution function"""
solution1 = Solution.generateRandomSolution(self.students,self.supervisors)
result = solution1.isValid(self.students,self.supervisors)
self.assertEqual(result,True)
def test_case11(self):
"""Testing the ERX Modified crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = crossover(solution1, solution2, self.supervisors,
self.supervisors2, self.students2)
structureResult = (solution3.getGraph().getStructure()
== solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== solution2.getGraph().getStructure())
result = (solution3.isValid(self.students2,
self.supervisors2)) and (structureResult)
self.assertTrue(result)
def test_case6(self):
"""Testing mutation function for a randomly created solution 2"""
mutationProbability = 0.3
swapProbability = 0.7
transferProbability = 0
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = mutate(solution1, self.supervisors, mutationProbability,
swapProbability, transferProbability)
result = solution2.isValid(self.students, self.supervisors)
self.assertTrue(result)
def initializePopulation(self,size):
"""
Function to create a pool of random solutions of a given size.
Used in the begining of the GA run to create intial population.
Parameters:
size (int) - the size of the population.
Returns:
population (list) - list containing 'n' randomly created Solution Objects, where n is the specified size.
"""
population = []
count = 0
while count < size:
#Generate random solution, calculate and set Fst and Fsup values, then append to population list until its of the size we want.
new = Solution.generateRandomSolution(self.students,self.supervisors)
new.calcFitness(self.students,self.supervisors,self.rankWeights,self.fitnessCache)
population.append(new)
count+=1
return population
