def greedy(points):
distance=find_distance(points) #creates n*n distance matrix
route = np.empty(0,dtype=int)
not_visited=np.ones(points.shape[0],dtype=bool) # True is point is not visited
not_visited[0]=0
route=np.append(route,0)
now=0
for i in range(points.shape[0]-1):
dis=distance[now][:]
nxt=next_point(not_visited,dis,points)
route=np.append(route,nxt)
not_visited[nxt]=0
now=nxt
route=np.append(route,0)
travel_distance=np.sum(find_segment_length(route,distance))
return (travel_distance,route)
def opt2(points):
distance=find_distance(points) # n*n distance matrix
route=np.arange(distance.shape[0]) # initilize route in chronological order
route=np.append(route,0) # final point is point zero (close loop)
segments=find_segment_length(route,distance) #length of each segment
flag=0
while flag ==0:
best_distance= np.sum(segments)
for i in range(1,route.shape[0]-2):
for j in range (i+1,route.shape[0]-1):
new_route=find_neighbour(route,i,j)
new_distance=np.sum(find_segment_length(new_route,distance))
if new_distance<best_distance:
best_distance=new_distance
route=new_route
i=1
j=1
flag=1
return (best_distance,route)
