def insert(self, i):
min_si = None
min_cost = math.inf
for si in range(self.n):
cost = basic.distance(self.xy, self.node_id(si), i)
cost += basic.distance(self.xy, self.node_id(si + 1), i)
cost -= self.next_length(si)
#print(cost)
assert (cost >= -1)
if cost < min_cost:
min_cost = cost
min_si = si
self.node_ids.insert(min_si + 1, i)
self.n += 1
def improve(xy, tour):
n = len(tour)
for i in range(n):
ilen = basic.distance(xy, tour[i], tour[(i + 1) % n])
for j in range(i + 2, n):
jlen = basic.distance(xy, tour[j], tour[(j + 1) % n])
cost = basic.distance(xy, tour[i], tour[j]) + basic.distance(
xy, tour[(i + 1) % n], tour[(j + 1) % n])
improvement = ilen + jlen - cost
if improvement > 0:
new_tour = swap(tour, i, j)
assert (tour != new_tour)
return new_tour, improvement
return tour, 0
def compute_sorted_edges(xy, node_id):
edges = []
for i in range(len(xy)):
if i == node_id:
continue
edges.append((basic.distance(xy, node_id, i), i))
edges.sort(reverse=True)
return edges
def length(xy, tour):
seen = set()
n = len(tour)
L = 0
for i in range(n):
L += basic.distance(xy, tour[i - 1], tour[i])
seen.add(tour[i])
assert (len(seen) == len(tour))
return L
def get_all_edges(xy):
"""Gets all (n-1)*(n)/2 edges. Returns list of tuples : (cost, (i, j))
i, j are the point IDs in the edge, in no particular order.
"""
edges = []
n = len(xy)
for i in range(n - 1):
for j in range(i + 1, n):
if i == j:
continue
edge = [i, j]
random.shuffle(edge)
edges.append((basic.distance(xy, i, j), edge))
return edges
def next_length(self, si):
assert (si < self.n and si >= 0)
return basic.distance(self.xy, self.node_id(si), self.node_id(si + 1))
def length(self, si, sj):
i = self.node_id(si)
j = self.node_id(sj)
return basic.distance(self.xy, i, j)
def sort_nearest(xy, ref_point):
ixy = []
for i in range(len(xy)):
ixy.append((i, xy[i]))
ixy.sort(key=lambda x: basic.distance(xy, x[0], ref_point))
return [x[0] for x in ixy][1:]
