k camions

france

@@ -0,0 +1,29 @@
+41 23
+45 35
+50 50
+40 60
+23 68
+30 68
+12 77
+35 78
+50 85
+60 85
+70 90
+80 100
+90 98
+100 90
+120 85
+130 83
+140 79
+130 70
+120 50
+130 45
+135 30
+120 20
+110 25
+100 29
+90 20
+80 15
+70 18
+60 17
+50 20

report.csv

@@ -1,105 +1,14 @@
 iterations,temps,distance,temperature
-5000,1.3165578842163086,121.21824428467325,0.6721111959865606
-10000,2.0787389278411865,97.8123419293458,0.4520495689035214
-15000,2.6385505199432373,97.8123419293458,0.3038679424228721
-20000,3.198474168777466,92.69046283557107,0.20426018026358692
-25000,3.757519245147705,91.51600752694644,0.13730379357770844
-30000,4.3160059452056885,91.51600752694644,9.23079397837336
-35000,4.877627372741699,91.51600752694644,6.204944249678936
-40000,5.4424684047698975,91.51600752694644,4.170966574687698
-45000,6.003183126449585,91.51600752694644,2.8037257817525405
-50000,6.564380168914795,91.51600752694644,1.8846658486714118
-55000,7.1275928020477295,91.51600752694644,1.2668733098884215
-60000,7.709557294845581,91.51600752694644,0.8515928616412607
-65000,8.272701740264893,91.51600752694644,0.572441140197534
-70000,8.83933424949646,91.51600752694644,0.3847952158254405
-75000,9.403577327728271,88.48277680334007,0.25865953322476637
-80000,9.963631629943848,88.48277680334007,0.17387106537833058
-85000,10.529204845428467,88.48277680334007,0.11687621561400502
-90000,11.091942071914673,88.48277680334007,7.857468750083974
-95000,11.65352463722229,88.48277680334007,5.28179435616188
-100000,12.218864679336548,88.48277680334007,3.5504247624892407
-105000,12.778974294662476,88.48277680334007,2.3865972705640917
-110000,13.341238498687744,88.48277680334007,1.6042718584101345
-115000,13.90438961982727,88.48277680334007,1.0783923318065296
-120000,14.464284658432007,88.48277680334007,0.7248958555263887
-125000,15.026023149490356,88.48277680334007,0.4872753504089352
-130000,15.591084957122803,88.46483730717296,0.32754673006611906
-135000,16.15230083465576,88.46483730717296,0.2201770729567358
-140000,16.71104145050049,88.46483730717296,0.14800313667002551
-145000,17.276767253875732,88.46483730717296,9.95009990004999
-150000,17.85395359992981,88.46483730717296,6.68846204380632
-155000,18.41609501838684,88.46483730717296,4.4959874735743215
-160000,18.976032257080078,86.96521115550244,3.022204989748841
-165000,19.537293672561646,86.96521115550244,2.031527679680444
-170000,20.10221004486084,86.96521115550244,1.3655939048829375
-175000,20.682851552963257,86.96521115550244,0.9179528941228919
-180000,21.248215913772583,86.96521115550244,0.6170483866511011
-185000,21.812267303466797,86.96521115550244,0.41478022881831517
-190000,22.361953496932983,86.96521115550244,0.2788154736977733
-195000,22.92663311958313,86.96521115550244,0.18741989847198132
-200000,23.475363969802856,86.96521115550244,0.12598374787951477
-205000,24.040228366851807,86.96521115550244,8.469758853683537
-210000,24.60388445854187,86.96521115550244,5.693376064774005
-215000,25.165529012680054,86.96521115550244,3.827090189332175
-220000,25.744653701782227,86.96521115550244,2.572571906483391
-225000,26.315173149108887,86.96521115550244,1.7292841000913133
-230000,26.881410598754883,86.96521115550244,1.1624256221146503
-235000,27.452577829360962,86.96521115550244,0.7813830745782491
-240000,28.007733821868896,86.96521115550244,0.5252460868220087
-245000,28.578561544418335,86.96521115550244,0.3530706777475832
-250000,29.141484260559082,86.96521115550244,0.2373342831345667
-255000,29.709417819976807,86.96521115550244,0.15953622178522642
-260000,30.27912664413452,86.96521115550244,0.10724032670439765
-265000,30.829555988311768,86.96521115550244,7.209657768279316
-270000,31.397671699523926,86.96521115550244,4.846335495759929
-275000,31.963274002075195,82.41100956304545,3.2577091024763214
-280000,32.53083896636963,82.41100956304545,2.1898336600184036
-285000,33.09827971458435,82.41100956304545,1.472007262681753
-290000,33.677080154418945,82.41100956304545,0.9894840055429684
-295000,34.242270946502686,82.41100956304545,0.6651316349089464
-300000,34.81053161621094,82.41100956304545,0.4471018119326612
-305000,35.37738299369812,82.41100956304545,0.3005420577549795
-310000,35.94760012626648,78.620704581794,0.2020245189549838
-315000,36.55578374862671,78.620704581794,0.13580098094712142
-320000,37.126696825027466,78.620704581794,9.129761418240957
-325000,37.694416999816895,78.620704581794,6.137030113095166
-330000,38.2617552280426,78.620704581794,4.12531465869275
-335000,38.828099727630615,78.620704581794,2.77303854138044
-340000,39.39502263069153,78.620704581794,1.864037870608908
-345000,39.95929265022278,78.620704581794,1.2530071728950798
-350000,40.52745842933655,78.620704581794,0.8422720375384076
-355000,41.09604501724243,78.620704581794,0.5661756776539253
-360000,41.66488742828369,78.620704581794,0.38058356882382527
-365000,42.25156593322754,78.620704581794,0.2558284620400366
-370000,42.81889510154724,78.620704581794,0.17196801793633615
-375000,43.38672590255737,78.620704581794,0.1155969861880494
-380000,43.95657014846802,78.620704581794,7.771467460721301
-385000,44.52591562271118,78.620704581794,5.2239842471781746
-390000,45.09210395812988,78.620704581794,3.511564778813712
-395000,45.65664196014404,78.620704581794,2.3604755704356934
-400000,46.24819898605347,78.620704581794,1.586712838743648
-405000,46.81594252586365,78.620704581794,1.0665891501555442
-410000,47.385974407196045,78.620704581794,0.7169617510187173
-415000,47.95387268066406,78.620704581794,0.4819420414588525
-420000,48.52208638191223,78.620704581794,0.3239616771682742
-425000,49.088802099227905,78.620704581794,0.21776719863656413
-430000,49.656049966812134,78.620704581794,0.14638321796742726
-435000,50.22277808189392,78.620704581794,9.8411944181564
-440000,50.79074048995972,78.620704581794,6.615255725344727
-445000,51.358076333999634,78.620704581794,4.4467781503197195
-450000,51.91084337234497,78.620704581794,2.989126458468149
-455000,52.478920459747314,78.620704581794,2.009292274693741
-460000,53.043365716934204,78.620704581794,1.350647254721015
-465000,53.60069131851196,78.620704581794,0.9079057485369901
-470000,54.16664910316467,78.620704581794,0.6102946904495621
-475000,54.73716902732849,78.620704581794,0.410240390911847
-480000,55.32295489311218,78.620704581794,0.2757637924254785
-485000,55.890077114105225,78.620704581794,0.18536855682068426
-490000,56.457499742507935,78.620704581794,0.12460483501317157
-495000,57.0232412815094,78.620704581794,8.37705594831087
-500000,57.5935537815094,78.620704581794,5.631061126214188
-505000,58.16193985939026,78.620704581794,3.785202057001227
-510000,58.728190183639526,78.620704581794,2.5444146833403267
-515000,59.27666735649109,78.620704581794,1.7103568008538028
-520000,59.84771800041199,78.620704581794,1.1497026822634422
+5000,0.6915416717529297,443.7492402983678,0.6721111959865606
+10000,1.3146755695343018,443.7492402983678,0.4520495689035214
+15000,1.7231664657592773,439.9078521514258,0.3038679424228721
+20000,2.1277782917022705,439.9078521514258,0.20426018026358692
+25000,2.5334930419921875,435.0390435921546,0.13730379357770844
+30000,2.973337411880493,435.0390435921546,9.23079397837336
+35000,3.3832550048828125,435.0390435921546,6.204944249678936
+40000,3.7914462089538574,435.0390435921546,4.170966574687698
+45000,4.204490900039673,435.0390435921546,2.8037257817525405
+50000,4.610482931137085,435.0390435921546,1.8846658486714118
+55000,5.0188446044921875,435.0390435921546,1.2668733098884215
+60000,5.4173479080200195,435.0390435921546,0.8515928616412607
+65000,5.86414647102356,435.0390435921546,0.572441140197534

sa.py

@@ -5,12 +5,13 @@
 parser = argparse.ArgumentParser()
 parser.add_argument("-d", help="dataset file", default=False)
 parser.add_argument("-n", help="noninteractive", default=False)
+parser.add_argument("-k", help="trucks", default=1)
 args = parser.parse_args()
 time_start = None
 report_file = open("report.csv", "w")
 
 # Déclaration de fonctions
-def generate_cities(howmany = 15, max_coordinates = 100):
+def generate_cities(howmany = 20, max_coordinates = 100):
     return [random.sample(range(max_coordinates), 2) for _ in range(howmany)]
 
 def generate_random_tour(cities):
@@ -50,6 +51,10 @@ def distance_between(tour, cities, i, j):
     city_count = len(cities)
     return sum([math.sqrt(sum([(cities[tour[(k+1) % city_count]][d] - cities[tour[k % city_count]][d])**2 for d in [0,1] ])) for k in [j,j-1,i,i-1]])
 
+def distance_to_next(tour, cities, index):
+    city_count = len(cities)
+    return sum([math.sqrt(sum([(cities[tour[(k+1) % city_count]][d] - cities[tour[k % city_count]][d])**2 for d in [0,1] ])) for k in [index]])
+
 def distance(tour, cities):
     city_count = len(cities)
     return sum([math.sqrt(sum([(cities[tour[(k+1) % city_count]][d] - cities[tour[k % city_count]][d])**2 for d in [0,1] ])) for k in range(city_count)])
@@ -158,4 +163,29 @@ def SA(cities, temperatures):
 report_file.close()
 
 # Affichage de détails
-explain_tour(tour, cities)
+explain_tour(tour, cities)
+
+# Division en k camions
+print("\nDivision en camions\n")
+k = int(args.k)
+tour_distance = distance(tour, cities)
+i = 0
+for truck in range(k-1):
+    distance_cumulee = 0
+    while distance_cumulee < (tour_distance / k):
+        curr = tour[i % city_count]
+        next = tour[(i + 1) % city_count]
+        distance = distance_to_next(tour, cities, i)
+
+        print("Entre {} et {} -> {}".format(cities[tour[i]], cities[tour[i+1]], distance))
+
+        distance_cumulee += distance
+        i += 1
+
+    tour.insert(i, tour[0])
+    tour.insert(i+1, tour[i+1])
+
+live_plot(tour, cities)
+
+while True:
+    time.sleep(1)