def top(n,members,cityList):
fitnessList = []
for member in members:
fitnessList.append(fitnessFunction.fitnessFunction(member, cityList))
# print fitnessFunction.fitnessFunction(member, cityList), " ", member
# print fitnessList
ans = []
ansFitness = []
insertedMembers = 0
memberCount = len(members)
for i in range(n):
ans.append(members[i])
ansFitness.append(fitnessList[i])
(ansFitness,ans) = quickSort(ansFitness, ans)
threshold = ansFitness[n - 1]
for j in range(n, memberCount):
if fitnessList[j] < threshold:
insertAtPosition(fitnessList[j], members[j], ansFitness, ans)
threshold = ansFitness[n - 1]
return ans
def createFitnessArray(pop, popSize, fitness):
i = 0
fitnessArray = []
while i < popSize:
function = fitnessFunction.fitnessFunction(pop[i])
fitness = function.run()
fitnessArray.append([pop[i], fitness])
print("Combined Fitness: " + str(fitness))
i += 1
return fitnessArray
def main(popSize, numOfIterations, mutationRate):
print('--------------------')
print('Creating Population')
print('--------------------')
bestFitness = []
fitnessArray = []
fitness = 0
#initialise population
pop = createNewPop(popSize)
fitnessArray = createFitnessArray(pop, popSize, fitness)
#fitnessArray = [[[1.77, 0.9], 0.55],[[4.54, 0.9], 0.55], [[4.54, 0.9], 0.5], [[1.77, 1.6], 0.38], [[1.77, 1.6], 0.38], [[4.66, 1.6], 0.35], [[0.83, 2.55], 0.33], [[4.66, 1.6], 0.33], [[4.66, 1.6], 0.33], [[1.77, 2.55], 0.3]]
#main loop
print('--------------------')
print('Starting Iterations')
print('--------------------')
i = 0
while i < numOfIterations:
crossoverPair = getTournamentPair(fitnessArray)
newMember = crossover(crossoverPair)
newMember = mutate(newMember, mutationRate)
del fitnessArray[-1]
function = fitnessFunction.fitnessFunction(newMember)
fitness = function.run()
newArr = [newMember, fitness]
fitnessArray.append(newArr)
fitnessArray = sort(fitnessArray)
bestFitness = fitnessArray[0]
for x in fitnessArray:
print(x)
print('--------------------')
print('Count: ' + str(i))
print('Best: ' + str(bestFitness))
print('--------------------')
i += 1
return bestFitness
pm_1 = 0.15
pm_2 = 0.01
# 种群初始化
chrom = []
fitness = 0
total = 0
pop = {}
for i in range(0, nPop):
pop[i] = Chrom(chrom, fitness, total)
for i in range(nPop):
pop[i].chrom = getIndividual(GeneSize, NodeSize, nodesInd)
pop[i].fitness, pop[i].total = fitnessFunction(pop[i].chrom, extra,
Velocities,
ConductivityMatrix, pipes,
nodesInd, con, demand)
# 保存最优 最差个体
pop = sorted(pop.iteritems(), key=lambda x: x[1].fitness, reverse=True)
bestIndividual = pop[0]
worstIndividual = pop[-1]
BestSolution = []
print bestIndividual[1].fitness
# 遗传操作
for it in range(0, MaxIt):
pop_c = {} # 交叉种群
for j in range(0, nc):
populationLimit = 100
population = []
population = randomLists.randomLists(populationLimit,cityCount)
for i in range(runs):
j = i + 1
print "Run#: ", j
print bestVal
newGeneration=[]
for j in range(populationLimit):
fitnessVal = fitnessFunction.fitnessFunction(population[j],city)
if fitnessVal < bestVal:
bestVal = fitnessVal
bestAns = population[j]
for k in range(populationLimit):
for l in range((k+1), populationLimit):
# child = population[k]
child = crossover.crossover(population[k],population[l],city)
newGeneration.append(child)
for member in newGeneration:
member = mutation.mutate(member)
for m in range(populationLimit):
newGeneration.append(population[m])
f = open('./ALL_tsp/a280.opt.tour')
line = f.readline()
while ((not(line is '')) and (line.find('TOUR_SECTION'))<0):
line=f.readline()
line=f.readline()
r=0
L=list()
L=line.split()
print L
val = int(L[0])
while(val > 0):
city.append(val)
line=f.readline()
L=line.split()
r = r+1
val = int(L[0])
coordinates = []
city = []
readFile(city)
print city
readInput.readFile(coordinates)
print coordinates
print "Optimum tour length is: ", fitnessFunction.fitnessFunction(city, coordinates)
