def fitness(individual, start, goal, vertexs_list):
"""
Determine the fitness of an individual. Lower is better.
individual: the individual to evaluate
start: start point
goal: goal point
vertexs_list: a list of vertexs of obstacles
"""
#TODO
previous_point = (start[0], start[1])
sum = 0.0
for point in individual:
sum += sqrt((point[0] - previous_point[0])**2 +
(point[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, point):
sum += 100 # depends on the scale of problem
previous_point = point
sum += sqrt((goal[0] - previous_point[0])**2 +
(goal[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, goal):
sum += 100
return sum
def optimal_operation(individual, vertexs_list, start, goal):
"""
genetic optimal operation
individual: the individual which need to be optimalize
vertexs_list: a list of vertexes of obstacles
start: start point
goal: end point
"""
# check whether start point can reach goal directly
cnt = 0
point_cnt = 0
best_individual = individual
for vertexs in vertexs_list:
if collision_detect(vertexs, start, goal):
point_cnt += 1
if point_cnt == 0:
best_individual = []
print best_individual
return best_individual
point_cnt = 0
for point in best_individual:
for vertexs in vertexs_list:
if collision_detect(vertexs, point, goal):
point_cnt += 1
if point_cnt == 0:
best_individual = best_individual[0:cnt + 1]
print best_individual
break
cnt += 1
return best_individual
def optimal_operation(individual, vertexs_list, start, goal):
"""
genetic optimal operation
individual: the individual which need to be optimalize
vertexs_list: a list of vertexes of obstacles
start: start point
goal: end point
"""
# check whether start point can reach goal directly
cnt = 0
point_cnt = 0
best_individual = individual
for vertexs in vertexs_list:
if collision_detect(vertexs, start, goal):
point_cnt += 1
if point_cnt == 0:
best_individual = []
print best_individual
return best_individual
point_cnt = 0
for point in best_individual:
for vertexs in vertexs_list:
if collision_detect(vertexs, point, goal):
point_cnt += 1
if point_cnt == 0:
best_individual = best_individual[0:cnt + 1]
print best_individual
break
cnt += 1
return best_individual
def fitness(individual,start, goal, vertexs_list):
"""
Determine the fitness of an individual. Lower is better.
individual: the individual to evaluate
target: the sum of numbers that individuals are aiming for
"""
#TODO
previous_point = (start[0], start[1])
sum = 0.0
for point in individual:
sum += sqrt((point[0] - previous_point[0])**2 +(point[1] - previous_point[1])**2 )
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, point):
sum += 100 # depends on the scale of problem
previous_point = point
sum += sqrt((goal[0] - previous_point[0])**2 + (goal[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, goal):
sum += 100
return sum
def fitness(individual, start, goal, vertexs_list):
"""
Determine the fitness of an individual. Lower is better.
individual: the individual to evaluate
target: the sum of numbers that individuals are aiming for
"""
#TODO
previous_point = (start[0], start[1])
sum = 0.0
for point in individual:
sum += sqrt((point[0] - previous_point[0])**2 +
(point[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, point):
sum += 100 # depends on the scale of problem
previous_point = point
sum += sqrt((goal[0] - previous_point[0])**2 +
(goal[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, goal):
sum += 100
return sum
def fitness(individual,start, goal, vertexs_list):
"""
Determine the fitness of an individual. Lower is better.
individual: the individual to evaluate
start: start point
goal: goal point
vertexs_list: a list of vertexs of obstacles
"""
#TODO
previous_point = (start[0], start[1])
sum = 0.0
for point in individual:
sum += sqrt((point[0] - previous_point[0])**2 +(point[1] - previous_point[1])**2 )
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, point):
sum += 100 # depends on the scale of problem
previous_point = point
sum += sqrt((goal[0] - previous_point[0])**2 + (goal[1] - previous_point[1])**2)
for vertexs in vertexs_list:
if collision_detect(vertexs, previous_point, goal):
sum += 100
return sum
