def main():
global BEST
nodes, temp = rgt.read("../graphs/graph_random_5.txt")
signal.signal(signal.SIGALRM, handler)
all_edge = []
plot_all_edge = []
plot_solution = []
counter = 0
for t in temp:
c, a, b = t.split(" ")
e = Edge.Edge(a, b, c)
all_edge.append(e)
gr_start = timeit.default_timer()
grasp_tree, grasp_cost, mincost = gra.grasp(nodes, temp)
gr_stop = timeit.default_timer()
print('Tree cost graph: ' + str(grasp_cost) + ' | time_GRASP: ' +
str(gr_stop - gr_start) + '\n' + 'Dijkstra cost: ' + str(mincost))
print('\n--- GRASP ---\n')
print_array(grasp_tree)
print('')
time = 0
j = 0
start = timeit.default_timer()
signal.setitimer(signal.ITIMER_REAL, 100, 50)
grasp_tree, bb = heu_cut(grasp_tree, all_edge, nodes)
stop = timeit.default_timer()
BEST = bb
time = stop - start
print('Cost_grasp: ' + str(mincost) + ' -------> cost_LS: ' + str(bb) +
' | time_LS: ' + str(time))
best_cost = bb
for i in range(15):
start = timeit.default_timer()
grasp_tree, bb = heu_cut(grasp_tree, all_edge, nodes)
stop = timeit.default_timer()
time = time + (stop - start)
print('Cost_grasp: ' + str(mincost) + ' -------> cost_LS: ' + str(bb) +
' | time_LS: ' + str(time))
if (j != 4):
if (bb > best_cost or bb == best_cost):
j += 1
best_cost = bb
elif (bb < best_cost):
best_cost = bb
BEST = best_cost
j = 0
else:
break
print('\n--- LS ---\n')
print_array(grasp_tree)
for e in all_edge:
v1, v2 = (e.v1, e.v2)
plot_all_edge.append((v1, v2))
for e in grasp_tree:
v1, v2 = (e.v1, e.v2)
plot_solution.append((v1, v2))
def main():
nodes,temp = rgt.read("../../graph/graph_random_3.txt")
all_edge = []
plot_all_edge = []
plot_solution = []
for t in temp:
c,a,b = t.split(" ")
e = cost_calc.Edge(a,b,c)
all_edge.append(e)
list_of_list_of_list =spt.loop_root_SPT(nodes,temp)
trees = []
for list_of_list in list_of_list_of_list:
temp_tree = []
for lis in list_of_list:
for ed in lis:
if(edge_in_list(ed,temp_tree)):
pass
else:
temp_tree.append(ed)
trees.append(temp_tree)
mincost = cost_calc.blabla(nodes,trees[0])
minpos = 0
i =0
for t in trees[1:]:
i+=1
c_temp = cost_calc.blabla(nodes,t)
if(c_temp < mincost):
mincost = c_temp
minpos = i
print("pre eu cost = "+str(mincost))
a = trees[minpos]
for e in all_edge:
v1,v2 = (e.v1,e.v2)
plot_all_edge.append((v1,v2))
tot = 0
for i in range(10):
start = timeit.default_timer()
a,b = heu_cut(a,all_edge,nodes)
stop = timeit.default_timer()
tot = tot + (stop - start)
print("cost = " + str(b) + ' time: ' + str(tot))
print_array(a)
for e in a:
v1,v2 = (e.v1,e.v2)
plot_solution.append((v1,v2))
toPlot.toPlot(nodes, plot_all_edge, plot_solution)
def main():
file_name = "../graphs/graph_ppt.txt"
nodes,temp = rgt.read(file_name)
all_edge = []
for t in temp:
c,a,b = t.split(" ")
all_edge.append(Edge.Edge(a,b,c))
#all_edge.sort(key = lambda x: x.cost)
arr_edge = []
arr_edge = gk.kruskal(all_edge)
#arr_edge = gk.grasp(all_edge)
mincost = util.blabla(nodes,arr_edge)
print("mincost first solution = "+str(mincost))
print("first solution")
util.print_array(arr_edge)
print("heuristic")
newcost= mincost
tot = 0
final_res,t = util.copy_array(arr_edge,mincost)
start = timeit.default_timer()
for i in range(50):
print(str(i+1)+"/50",end="\r")
arr_edge,newcost= heuristic(arr_edge,newcost,all_edge,nodes)
print("step "+str(i+1)+" solution to optimize cost = "+str(newcost))
stop = timeit.default_timer()
tot += stop-start
print("time = "+str(tot))
start = timeit.default_timer()
if(mincost> newcost):
mincost = newcost
final_res = arr_edge
elif(mincost == newcost):
break
print("result = "+str(mincost))
util.print_array(arr_edge)
'''plot_all_edge = []
def main():
nodes,temp = rgt.read("../graphs/graph_2.txt")
all_edge = []
for t in temp:
c,a,b = t.split(" ")
e = Edge.Edge(a,b,c)
all_edge.append(e)
list_of_list_of_list =spt.loop_root_SPT(nodes,temp)
trees = []
for list_of_list in list_of_list_of_list:
temp_tree = []
for lis in list_of_list:
for ed in lis:
if(util.edge_in_list(ed,temp_tree)):
pass
else:
temp_tree.append(ed)
trees.append(temp_tree)
mincost = util.blabla(nodes,trees[0])
minpos = 0
i =0
for t in trees[1:]:
i+=1
c_temp = util.blabla(nodes,t)
if(c_temp < mincost):
mincost = c_temp
minpos = i
print("pre eu cost = "+str(mincost))
a = trees[minpos]
mincost = util.blabla(nodes,a)
for i in range(10):
a,b = heu_cut(a,all_edge,nodes)
print("cost = "+str(b))
if(b<mincost):
mincost = b
elif(b == mincost):
break
util.print_array(a)
for i in nodes:
if (i != root):
cost, path = dk.shortest_path(graph, root, i, flag)
list.append(path)
return list
def loop_root_SPT(nodes, edges):
list = []
for i in nodes:
list.append(tree_dijk(i, nodes, edges))
return list
if __name__ == '__main__':
list = []
list2 = []
nodes = []
edges = []
nodes, edges = rd.read('graph_1.txt')
list = tree_dijk('B', nodes, edges)
list2 = loop_root_SPT(nodes, edges)
print(list)
print('\n')
print(list2)
def main():
nodes, temp = rgt.read("../graph/graph_1.txt")
all_edge = []
for t in temp:
c, a, b = t.split(" ")
all_edge.append(cost_calc.Edge(a, b, c))
all_edge.sort(key=lambda x: x.cost)
arr_edge = []
free_edge = []
for e in all_edge:
arr_edge.append(e)
a, b = cost_calc.cic(arr_edge)
if (a):
arr_edge.pop()
free_edge.append(e.copy())
mincost = cost_calc.blabla(nodes, arr_edge)
solution_array = []
solution_array.append(copy_array(arr_edge, mincost))
heuristic(arr_edge, all_edge, nodes, solution_array)
i = 0
welcome_to_matrix_neo = []
res = []
merge(res, solution_array)
for arr, c in solution_array:
if (i == 0):
i += 1
continue
sol = []
sol.append(copy_array(arr, c))
heuristic(arr, all_edge, nodes, sol)
merge(res, sol)
welcome_to_matrix_neo.append(sol)
welcome_to_matrix_neo.insert(0, solution_array)
i = 0
#print_all_solution(solution_array)
'''for arr,c in res:
i+=1
print("\niterazione n = "+str(i)+" costo = "+str(c)+"\n")
print_array(arr)'''
mincost = 9000
minpos = -1
i = 0
for a, c in res:
if (mincost > c):
mincost = c
minpos = i
i += 1
print("best solution cost = " + str(mincost))
a, b = res[minpos]
print_array(a)
plot_all_edge = []
for e in all_edge:
v1, v2 = (e.v1, e.v2)
plot_all_edge.append((v1, v2))
plot_solution = []
for e in a:
v1, v2 = (e.v1, e.v2)
plot_solution.append((v1, v2))
toPlot.toPlot(nodes, plot_all_edge, plot_solution)
'''f.write(str(res))