def run():
try:
argp = argparse.ArgumentParser(description='AMMM Lab Heuristics')
argp.add_argument('configFile', help='configuration file path')
args = argp.parse_args()
print 'AMMM Lab Heuristics'
print '-------------------'
print 'Reading Config file %s...' % args.configFile
config = DATParser.parse(args.configFile)
ValidateConfig.validate(config)
print 'Reading Input Data file %s...' % config.inputDataFile
inputData = DATParser.parse(config.inputDataFile)
ValidateInputData.validate(inputData)
print 'Creating Problem...'
problem = Problem(inputData)
if (problem.checkInstance()):
print 'Solving Problem...'
solver = None
solution = None
if (config.solver == 'Greedy'):
solver = Solver_Greedy()
solution = solver.solve(config, problem)
elif (config.solver == 'GRASP'):
solver = Solver_GRASP()
solution = solver.solve(config, problem)
elif (config.solver == 'BRKGA'):
solver = Solver_BRKGA()
decoder = TaskToCPUAssignment_Decoder(config, problem)
solution = solver.solve(config, problem, decoder)
solution.saveToFile(config.solutionFile)
else:
print 'Instance is infeasible.'
solution = Solution.createEmptySolution(config, problem)
solution.makeInfeasible()
solution.saveToFile(config.solutionFile)
return (0)
except Exception as e:
print
print 'Exception:', e
print
return (1)
def run():
argp = argparse.ArgumentParser(description='AMMM Lab Heuristics')
argp.add_argument('configFile', help='configuration file path')
args = argp.parse_args()
start_time = time.time()
print 'AMMM Lab Heuristics'
print '-------------------'
print 'Reading Config file %s...' % args.configFile
config = DATParser.parse(args.configFile)
#ValidateConfig.validate(config)
print 'Reading Input Data file %s...' % config.inputDataFile
inputData = DATParser.parse(config.inputDataFile)
# ValidateInputData.validate(inputData)
print 'Creating Problem...'
problem = Problem(inputData)
if problem.checkInstance():
print 'Solving Problem...'
solver = None
solution = None
if config.solver == 'Greedy':
print 'Greedy solving'
greedySolver = Greedy(config, problem)
solutionGreedy = greedySolver.computeCandidates()
candidates = solutionGreedy[0]
cost = solutionGreedy[1]
for candService in candidates:
print candService.getBus()
print candService.getDriver()
print cost
# Start local search
local_search = LocalSearch()
solution_log = []
solution = greedySolver
for i in xrange(1000):
solution_log.append(solution)
solution = local_search.exploreNeighborhoodMixed(solution)
print "Iteration %d with cost %f" % (i + 1,
solution.calculateCosts())
print "Best solution had %f cost" % solution.calculateCosts()
print "Time: %f" % (time.time() - start_time)
elif config.solver == 'GRASP':
#solver = GRASP()
solution = solver.solve(config, problem)
#solution.saveToFile(config.solutionFile)
else:
print 'Instance is infeasible.'
#solution = Solution.createEmptySolution(config, problem)
#solution.makeInfeasible()
#solution.saveToFile(config.solutionFile)
return (0)
