van boeren - 10 months ago 46

Python Question

This code suppose to reduce the distance of initial tour: distan(initial_tour) < distan(best) . Can you help me plz? I 've been trying all day now. **Do I need to change my swapping method?**

Something goes wrong and the simulated annealing does'not work:

`def prob(currentDistance,neighbourDistance,temp):`

if neighbourDistance < currentDistance:

return 1.0

else:

return math.exp( (currentDistance - neighbourDistance) / temp)

def distan(solution):

#gives the distance of solution

listax, listay = [], []

for i in range(len(solution)):

listax.append(solution[i].x)

listay.append(solution[i].y)

dists = np.linalg.norm(np.vstack([np.diff(np.array(listax)), np.diff(np.array(listay))]), axis=0)

cumsum_dist = np.cumsum(dists)

return cumsum_dist[-1]

#simulated annealing

temp = 1000000

#creating initial tour

shuffle(greedys)

initial_tour=greedys

print (distan(initial_tour))

current_best = initial_tour

best = current_best

while(temp >1 ):

#create new neighbour tour

new_solution= current_best

#Get a random positions in the neighbour tour

tourPos1=random.randrange(0, len(dfar))

tourPos2=random.randrange(0, len(dfar))

tourCity1=new_solution[tourPos1]

tourCity2=new_solution[tourPos2]

#swapping

new_solution[tourPos1]=tourCity2

new_solution[tourPos2]=tourCity1

#get distance of both current_best and its neighbour

currentDistance = distan(current_best)

neighbourDistance = distan(new_solution)

# decide if we should accept the neighbour

# random.random() returns a number in [0,1)

if prob(currentDistance,neighbourDistance,temp) > random.random():

current_best = new_solution

# keep track of the best solution found

if distan(current_best) < distan(best):

best = current_best

#Cool system

temp = temp*0.99995

print(distan(best))

Answer Source

Your problem is in the first line of your `while`

loop, where you write

```
new_solution= current_best
```

What this does is puts a reference to the `current_best`

list into `new_solution`

. This means that when you change `new_solution`

, you're actually changing `current_best`

as well, which was not your intention.

The problem could be solved by replacing the problematic line with one that copies the list into a new list, like so:

```
new_solution = list(current_best)
```