felixm/discrete_optimization
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Felix Martin
2020-01-15 13:05:00 -05:00
parent c690d56cb9
commit 955f1def0b
2 changed files with 24 additions and 13 deletions
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4
tsp/map.py
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@@ -6,7 +6,7 @@ class Map(object):
# and neighbor regions. We can actually cluster in O(n) when we know how # and neighbor regions. We can actually cluster in O(n) when we know how
# high and wide the clusters are. Once we have that working we go from # high and wide the clusters are. Once we have that working we go from
# there # there
CLUSTER_SIZE = 3 # How many points we want per cluster. CLUSTER_SIZE = 5 # How many points we want per cluster.
def __init__(self): def __init__(self):
pass pass
@@ -131,7 +131,7 @@ class Map(object):
def plot_points(): def plot_points():
for i, p in enumerate(points): for i, p in enumerate(points):
plt.plot(p.x, p.y, '') plt.plot(p.x, p.y, '')
plt.text(p.x, p.y, ' ' + str(p)) # plt.text(p.x, p.y, ' ' + str(p))
for nb, _ in p.neighbors: for nb, _ in p.neighbors:
# plt.plot([p.x, nb.x], [p.y, nb.y], 'r--') # plt.plot([p.x, nb.x], [p.y, nb.y], 'r--')
pass pass

33
tsp/tsp.py
View File

@@ -62,9 +62,7 @@ class Point(object):
def __str__(self): def __str__(self):
# m = "P_{}({}, {})".format(self.index, self.x, self.y) # m = "P_{}({}, {})".format(self.index, self.x, self.y)
# m = "P_{}({}, {})".format(self.index, self.cluster_x, self.cluster_y) # m = "P_{}({}, {})".format(self.index, self.cluster_x, self.cluster_y)
id = self.id m = "P(id={}, index={})".format(self.id, self.index)
index = self.index
m = f"P({id=}, {index=})"
return m return m
def __repr__(self): def __repr__(self):
@@ -151,14 +149,16 @@ def k_opt(p1, route):
return steps return steps
def local_search_k_opt(route): def local_search_k_opt(route, goal):
current_total = route.total_distance current_total = route.total_distance
no_improvement_iterations = 0 no_improvement_iterations = 0
while no_improvement_iterations < 5: while no_improvement_iterations < 8:
no_improvement_iterations += 1 print("{} {}".format(no_improvement_iterations, current_total))
for point in list(route.points): for point in list(route.points):
before_k_opt = current_total before_k_opt = current_total
steps = k_opt(point, route) steps = k_opt(point, route)
if not steps: if not steps:
continue continue
@@ -168,6 +168,7 @@ def local_search_k_opt(route):
# the neighborhood faster. # the neighborhood faster.
for i in range(len(steps), 0, -1): for i in range(len(steps), 0, -1):
current_total = route.swap(*steps[i - 1][1]) current_total = route.swap(*steps[i - 1][1])
assert(float_is_equal(before_k_opt, current_total)) assert(float_is_equal(before_k_opt, current_total))
new_total = min(steps, key=lambda t: t[0])[0] new_total = min(steps, key=lambda t: t[0])[0]
@@ -178,9 +179,14 @@ def local_search_k_opt(route):
if total == new_total: if total == new_total:
break break
assert(float_is_equal(route.total_distance, current_total)) assert(float_is_equal(route.total_distance, current_total))
no_improvement_iterations = 0
# if no_improvement_iterations > 2: no_improvement_iterations += 1
# current_total = route.swap(choice(route.points), choice(route.points)) if no_improvement_iterations > 3:
current_total = route.swap(choice(route.points), choice(route.points))
if current_total < goal:
return
class Route(object): class Route(object):
@@ -298,11 +304,14 @@ class Route(object):
def solve_it(input_data): def solve_it(input_data):
r = Route(parse_input_data(input_data)) r = Route(parse_input_data(input_data))
m = Map() m = Map()
goal = {51: 429,
100: 20800,
200: 30000,
574: 39000}[r.len_points]
m.cluster(r.points) m.cluster(r.points)
# r.reorder_points_greedy() local_search_k_opt(r, goal)
local_search_k_opt(r) m.plot(r.points)
# m.plot(r.points)
r.verify_total_distance() r.verify_total_distance()
return prepare_output_data(r.points) return prepare_output_data(r.points)
@@ -310,7 +319,9 @@ def solve_it(input_data):
if __name__ == "__main__": if __name__ == "__main__":
file_location = "data/tsp_51_1" file_location = "data/tsp_51_1"
file_location = "data/tsp_100_3"
file_location = "data/tsp_200_2" file_location = "data/tsp_200_2"
# file_location = "data/tsp_574_1"
# file_location = "data/tsp_6_1" # file_location = "data/tsp_6_1"
with open(file_location, 'r') as input_data_file: with open(file_location, 'r') as input_data_file:
input_data = input_data_file.read() input_data = input_data_file.read()