如何获得在VRP问题中计算出的所有解？

问题描述

我正在使用ortools优化路线，并且在尝试针对某些特定条件进行优化并在计算出vrp问题的解决方案后为用户提供输出选项时遇到问题。

要做到这一点，我想出的解决方案是解决最佳路线问题，并保留所有解决方案，这样我以后便可以仔细研究并检查其中的任何一个，并满足其中的某些特定条件并将其分开。所以我的问题是，如何保存所有在python列表中得到的解决方案？

我尝试使用收集器，但没有成功，该部分在这里：

def main():
"""Solve the VRP with time windows."""
data = create_data_model()

# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),data['num_vehicles'],data['starts'],data['ends'])

# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
solver = routing.solver()
collector = solver.AllSolutionCollector()
routing.AddSearchMonitor(collector)

我的期望是，有了这个收集器对象，我可以访问所有解决方案并将它们放在类似以下的列表中：

解决方案= [[0，3，1，2]，[0，2，3，1]，[0，1，3，2]]

BestSolution = [0，1，3，2]

让我知道你们需要我发布些什么来帮助我。感谢您的提前帮助。

完整代码：

def main():
"""Solve the VRP with time windows."""
#start = timee.clock()
# Instantiate the data problem.
data = create_data_model()

# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),data['ends'])

# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
solver = routing.solver()
collector = solver.AllSolutionCollector()
routing.AddSearchMonitor(collector)
#sm     = pywrapcp.SearchMonitor(solver)
#collector = pywrapcp.solutionCollector(sm)




# Create and register a transit callback.
def time_callback(from_index,to_index):
    """Returns the travel time between the two nodes."""
    # Convert from routing variable Index to time matrix NodeIndex.
    from_node = manager.IndexToNode(from_index)
    to_node = manager.IndexToNode(to_index)
    return data['time_matrix'][from_node][to_node]

transit_callback_index = routing.RegisterTransitCallback(time_callback)

# Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

start_time = timee()
solution_curve = list()
COST_MULTIPLIER = 1e4
def record_solution():
    t = timee() - start_time
    solution_curve.append((t,routing.Costvar().Max() / COST_MULTIPLIER))
routing.AddAtSolutionCallback(record_solution)

# Add Time Windows constraint.
time = 'Time'
routing.AddDimension(
    transit_callback_index,# allow waiting time
    15000,# maximum time per vehicle
    False,# Don't force start cumul to zero.
    time)
time_dimension = routing.GetDimensionorDie(time)
time_dimension.SetGlobalSpanCostCoefficient(1)


# Instantiate route start and end times to produce feasible times.
for i in range(data['num_vehicles']):
    routing.AddVariableMinimizedByFinalizer(
        time_dimension.CumulVar(routing.Start(i)))
    routing.AddVariableMinimizedByFinalizer(
        time_dimension.CumulVar(routing.End(i)))

# Setting first solution heuristic.
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
    routing_enums_pb2.FirstSolutionStrategy.PATH_CHEApest_ARC)

# Solve the problem.
solution = routing.solveWithParameters(search_parameters)

#print(f'COLLECTION = {collector.solution(0)}')

if solution:
    for i in range(collector.solutionCount()):
        solution_n = collector.solution(i)
        print_solution(data,manager,routing,solution_n)
        routes = get_routes(solution_n,manager)
        # display the routes.
        for i,route in enumerate(routes):
            print('Route',i,route)

解决方法

暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！

如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。

小编邮箱:dio#foxmail.com (将#修改为@）

or-tools python