Upload Ejecucion.py
Browse files- pages/Ejecucion.py +108 -0
pages/Ejecucion.py
ADDED
|
@@ -0,0 +1,108 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import streamlit as st
|
| 2 |
+
|
| 3 |
+
from pages.vrp.Origen import Grafo, Vehiculos
|
| 4 |
+
from pages.vrp.Algoritmo_gen茅tico import Algoritmo_Genetico
|
| 5 |
+
|
| 6 |
+
#######################
|
| 7 |
+
## FUNCIONES AUXILIARES
|
| 8 |
+
#######################
|
| 9 |
+
|
| 10 |
+
def grafar(reparto : list[list[int]]):
|
| 11 |
+
|
| 12 |
+
result = "digraph { \n"
|
| 13 |
+
|
| 14 |
+
for ruta in reparto:
|
| 15 |
+
result += "Almac茅n ->"
|
| 16 |
+
for nodo in ruta:
|
| 17 |
+
result += str(nodo) + "\n"
|
| 18 |
+
result += str(nodo) + "->"
|
| 19 |
+
result += "Almac茅n \n"
|
| 20 |
+
|
| 21 |
+
result += "}"
|
| 22 |
+
|
| 23 |
+
return result
|
| 24 |
+
|
| 25 |
+
def presentar(reparto : list[list[int]]):
|
| 26 |
+
|
| 27 |
+
result = ""
|
| 28 |
+
|
| 29 |
+
for i in range(len(reparto)):
|
| 30 |
+
result += "Camion " + str(i) + ": " + "Almac茅n -> "
|
| 31 |
+
for parada in reparto[i]:
|
| 32 |
+
result += str(parada) + " -> "
|
| 33 |
+
result += "Almac茅n \n"
|
| 34 |
+
|
| 35 |
+
return result
|
| 36 |
+
|
| 37 |
+
st.set_page_config(page_title="LupercAI", page_icon= "馃殯")
|
| 38 |
+
|
| 39 |
+
st.title("LupercAI 馃殯")
|
| 40 |
+
|
| 41 |
+
valores_vitales = ["distancias", "demandas_clientes", "capacidad_vehiculos"]
|
| 42 |
+
importado = True
|
| 43 |
+
for valor in valores_vitales: importado = importado and valor in st.session_state
|
| 44 |
+
|
| 45 |
+
if not importado:
|
| 46 |
+
st.warning("Faltan datos", icon="鈿狅笍")
|
| 47 |
+
else:
|
| 48 |
+
#if "num_nodos" not in st.session_state: st.session_state["num_nodos"] = len(st.session_state["demandas_clientes"])
|
| 49 |
+
#if "num_vehiculos" not in st.session_state: st.session_state["num_vehiculos"] = len(st.session_state["capacidad_vehiculos"])
|
| 50 |
+
|
| 51 |
+
grafo = Grafo(st.session_state["distancias"], st.session_state["demandas_clientes"])
|
| 52 |
+
vehiculos = Vehiculos(st.session_state["capacidad_vehiculos"])
|
| 53 |
+
|
| 54 |
+
if "activar_generaciones" in st.session_state:
|
| 55 |
+
if st.session_state["activar_generaciones"]:
|
| 56 |
+
if "alg_genetico" not in st.session_state: st.session_state["alg_genetico"] = Algoritmo_Genetico(tamano_poblacion = st.session_state["tamano_poblacion"],
|
| 57 |
+
generaciones = st.session_state["generaciones"], tamano_torneo = st.session_state["tamano_torneo"],
|
| 58 |
+
crossover_prob = st.session_state["crossover_prob"], mutation_prob = st.session_state["mutation_prob"])
|
| 59 |
+
else:
|
| 60 |
+
if "alg_genetico" not in st.session_state: st.session_state["alg_genetico"] = Algoritmo_Genetico()
|
| 61 |
+
else:
|
| 62 |
+
if "alg_genetico" not in st.session_state: st.session_state["alg_genetico"] = Algoritmo_Genetico()
|
| 63 |
+
|
| 64 |
+
alg_genetico = st.session_state["alg_genetico"]
|
| 65 |
+
|
| 66 |
+
from threading import Thread
|
| 67 |
+
Thread(target=alg_genetico.generar, args = (grafo, vehiculos)).start()
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
#Computaci贸n:
|
| 71 |
+
|
| 72 |
+
empty_latest_iteration = st.empty()
|
| 73 |
+
empty_mejor_coste = st.empty()
|
| 74 |
+
|
| 75 |
+
st.subheader("Barra de progreso")
|
| 76 |
+
barra_progreso = st.progress(0)
|
| 77 |
+
|
| 78 |
+
st.subheader("Grafo del mejor recorrido actual")
|
| 79 |
+
|
| 80 |
+
empty_txt = st.empty()
|
| 81 |
+
|
| 82 |
+
empty_grafo = st.empty()
|
| 83 |
+
|
| 84 |
+
i = 0
|
| 85 |
+
while alg_genetico.generacion_actual < alg_genetico.generaciones:
|
| 86 |
+
#Generaci贸n por escrito
|
| 87 |
+
empty_latest_iteration.write("Generaci贸n: " + str(alg_genetico.generacion_actual))
|
| 88 |
+
|
| 89 |
+
#Barra de progreso
|
| 90 |
+
barra_progreso.progress( alg_genetico.generacion_actual/alg_genetico.generaciones)
|
| 91 |
+
|
| 92 |
+
#Mejor coste actual (texto)
|
| 93 |
+
empty_mejor_coste.write("**Mejor coste**: " + str(alg_genetico.mejor_candidato[1]))
|
| 94 |
+
|
| 95 |
+
#Descarga de grafo
|
| 96 |
+
empty_txt.download_button("Mejor recorrido 馃斀", presentar(alg_genetico.mejor_candidato[0]), file_name="Mejor reparto - Generacion " + str(alg_genetico.generacion_actual) + ".txt", key=str(i))
|
| 97 |
+
i += 1
|
| 98 |
+
|
| 99 |
+
#Mostrar el grafo
|
| 100 |
+
empty_grafo.graphviz_chart(grafar(alg_genetico.mejor_candidato[0]))
|
| 101 |
+
|
| 102 |
+
|
| 103 |
+
#Ultima iteracion
|
| 104 |
+
empty_latest_iteration.write("Generaci贸n: " + str(alg_genetico.generacion_actual))
|
| 105 |
+
barra_progreso.progress( alg_genetico.generacion_actual/alg_genetico.generaciones)
|
| 106 |
+
empty_mejor_coste.write("**Mejor coste**: " + str(alg_genetico.mejor_candidato[1]))
|
| 107 |
+
empty_txt.download_button("Mejor recorrido 馃斀", presentar(alg_genetico.mejor_candidato[0]), file_name="Mejor reparto - Generacion " + str(alg_genetico.generacion_actual) + ".txt", key=str(i))
|
| 108 |
+
empty_grafo.graphviz_chart(grafar(alg_genetico.mejor_candidato[0]))
|