def TSP(stops, Alg, steps, param, seed=None, coordfile='xycoords.txt'):
'''A wrapper function that attempts to optimize the traveling
salesperson problem using a specified algorithm. If coordfile
exists, a preexisting set of coordinates will be used. Otherwise,
a new set of "stops" coordinates will be generated for the person to
traverse, and will be written to the specified file.'''
# Create the distance matrix, which will be used to calculate
# the fitness of a given path
if os.path.isfile(coordfile):
coords = scipy.genfromtxt(coordfile)
distMat = DistanceMatrix(coords)
else:
distMat = GenerateMap(stops, fname=coordfile, seed=seed)
if Alg == 'HC':
# param is the number of solutions to try per step
bestSol, fitHistory = hc.HillClimber(steps, param, distMat, seed)
elif Alg == 'SA':
# param is a placeholder
bestSol, fitHistory = sa.SimulatedAnnealing(steps, param, distMat,
seed)
elif Alg == 'MC3':
# param is the number of chains
bestSol, fitHistory = mc3.MCMCMC(steps, param, distMat, seed)
elif Alg == 'GA':
# param is the population size
bestSol, fitHistory = ga.GeneticAlgorithm(steps, param, distMat, seed)
else:
raise ValueError('Algorithm must be "HC", "SA", "MC3", or "GA".')
outfname = coordfile + '-' + Alg + '-' + \
str(steps) + '-' + str(param) + '.txt'
scipy.savetxt(outfname, scipy.array(bestSol), fmt='%i')
return bestSol, fitHistory
# Quality: Overall shortest tour found
# Route: Array of node_ids in order of travel [node_1,node_2,...]
if options.method == "BnB":
branch = BranchAndBound.BranchAndBound(cities, options.cutoff)
branch.main()
quality = branch.minimum
route = branch.bestSolution
trace = branch.trace
elif options.method == "Approx":
trace, quality, route = construction_heuristic.nearest_neighbor(
params, cities, options.cutoff)
elif options.method == "LS1":
s = SA.SimulatedAnnealing(
cities,
0.00001) # the second argument is the cooling rate, default is 0.001.
s.anneal(options.cutoff)
quality = s.best_distance
route = s.best_route
trace = s.trace
elif options.method == "LS2":
g = genetic.genetic(params, cities, options.cutoff)
trace, quality, route = g.evolve()
#### ########## ####
print(quality)
for id in route:
print(id, end=" ")
print("")
