iterations, choosing elite and good solutions

Author: mackoo13

app/main.py

@@ -26,14 +26,16 @@ def print_solution_pool(pool):
 
 
 def best_in_neighbourhood(solution, radius, number_of_bees):
- neighbours = [solution.random_neighbour(radius) for _ in range(number_of_bees)]
+ neighbours = []
+ for _ in range(number_of_bees):
+ neighbours.append(solution.random_neighbour(radius))
  best_neighbour = min(neighbours, key=lambda s: s.evaluate())
  return best_neighbour if best_neighbour.evaluate() < solution.evaluate() else solution
 
 
 def main():
 
- n = 10
+ n = 5
  m = 3
  e = 1
  nep = 4
@@ -46,9 +48,7 @@ def main():
 
  # bee = Solution(data, {data.servers[0]: [data.movies[0]], data.servers[1]: [data.movies[1]]})
  # print(bee)
- # print(bee.evaluate())
  # print(bee.random_neighbour(1))
- # print(bee.random_neighbour(1).evaluate())
 
  pool = [random_solution(data) for _ in range(n)]
 
@@ -71,8 +71,6 @@ def main():
  for _ in range(n-m):
  pool.append(random_solution(data))
 
- # print_solution_pool(pool)
-
 
 if __name__ == '__main__':
  main()

app/solution.py

@@ -17,22 +17,28 @@ def __str__(self):
  res += str(self.evaluate())
  return res
 
+ def __copy__(self):
+ res = Solution(self.data, dict(self.solution))
+ for l in res.solution:
+ res.solution[l] = list(res.solution[l])
+ return res
+
  def random_neighbour(self, radius):
 
+ res = self.__copy__()
  if radius == 0:
- return self
+ return res
 
  acceptable_ops = [(s, f)
- for s in self.data.servers
- for f in self.data.movies
- if f in self.solution[s] or f.size <= self.free_space(s)]
+ for s in res.data.servers
+ for f in res.data.movies
+ if f in res.solution[s] or f.size <= res.free_space(s)]
 
  op = random.choice(acceptable_ops)
  s = op[0]
  f = op[1]
 
- res = Solution(self.data, self.solution)
- if f in self.solution[s]:
+ if f in res.solution[s]:
  res.solution[s].remove(f)
  else:
  res.solution[s].append(f)