帮我优化这段代码：def readCSVFile(demand_file,depot_file,model): with open(demand_file,'r') as f: demand_reader=csv.DictReader(f) for row in demand_reader: demand = Demand() demand.id = int(row['id']) demand.x_coord = float(row['x_coord']) demand.y_coord = float(row['y_coord']) demand.demand = float(row['demand']) demand.start_time=float(row['start_time']) demand.end_time=float(row['end_time']) demand.service_time=float(row['service_time']) model.demand_dict[demand.id] = demand model.demand_id_list.append(demand.id) model.number_of_demands=len(model.demand_id_list) with open(depot_file, 'r') as f: depot_reader = csv.DictReader(f) for row in depot_reader: vehicle = Vehicle() vehicle.depot_id = row['depot_id'] vehicle.x_coord = float(row['x_coord']) vehicle.y_coord = float(row['y_coord']) vehicle.type = row['vehicle_type'] vehicle.capacity=float(row['vehicle_capacity']) vehicle.free_speed=float(row['vehicle_speed']) vehicle.numbers=float(row['number_of_vehicle']) vehicle.fixed_cost=float(row['fixed_cost']) vehicle.variable_cost=float(row['variable_cost']) vehicle.start_time=float(row['start_time']) vehicle.end_time=float(row['end_time']) model.vehicle_dict[vehicle.type] = vehicle model.vehicle_type_list.append(vehicle.type)

depot_tools

"depot_tools" 是一个专为开发者设计的工具集合，主要在Google开源项目中广泛使用。这个工具包包含了用于版本控制、构建、测试等不同任务的实用程序，旨在简化和加速开发过程。在这个最新的"refs_heads_main"主分支...

depot_tools_2017.3.24（禁止cipd更新）

"depot_tools_2017.3.24（禁止cipd更新）"这个压缩包文件包含了Chromium项目的开发工具集，depot_tools，专为Windows操作系统设计。Chromium是一个开源的浏览器项目，它是Google Chrome的基础，对于Web开发者和...

帮我优化这段代码：def readCSVFile（demand_file，depot_file，model）： with open（demand_file，'r'） as f： demand_reader=csv.demand_reader 中行的 DictReader（f）：需求 = 需求（） demand.id = int（row['id']） demand.x_coord = float（row['x_coord']） demand.y_coord = float（row['y_coord']） demand.demand = float（row['demand']） demand.start_time=float（row['start_time']） demand.end_time=float（row['end_time']） demand.service_time=float（row['service_time']） model.demand_dict[demand.id] = 需求 model.demand_id_list.append（demand.id） model.number_of_demands=len（model.demand_id_list） with open（depot_file， 'r'）作为 f： depot_reader = csv。depot_reader 中行的字典阅读器（f）：车辆 = 车辆（） vehicle.depot_id = 行['depot_id'] vehicle.x_coord = float（row['x_coord']） vehicle.y_coord = float（row['y_coord']） vehicle.type = row['vehicle_type'] vehicle.capacity=float（row['vehicle_capacity']） vehicle.free_speed=float（row['vehicle_speed']） vehicle.numbers=float（row['number_of_vehicle']） vehicle.fixed_cost=float（row['fixed_cost']） vehicle.variable_cost=float（row['variable_cost']） vehicle.start_time=float（row['start_time']） vehicle.end_time=float（row['end_time']） model.vehicle_dict[vehicle.type] = Vehicle model.vehicle_type_list.append（vehicle.type）

def readCSVFile(demand_file, depot_file, model): demand_df = pd.read_csv(demand_file) demand_df['id'] = demand_df['id'].astype(int) demand_df['x_coord'] = demand_df['x_coord'].astype(float) demand...

优化这段代码：def readCSVFile(demand_file,depot_file,model): with open(demand_file,'r') as f: demand_reader=csv.DictReader(f) for row in demand_reader: demand = Demand() demand.id = int(row['id']) demand.x_coord = float(row['x_coord']) demand.y_coord = float(row['y_coord']) demand.demand = float(row['demand']) demand.start_time=float(row['start_time']) demand.end_time=float(row['end_time']) demand.service_time=float(row['service_time']) model.demand_dict[demand.id] = demand model.demand_id_list.append(demand.id) model.number_of_demands=len(model.demand_id_list) with open(depot_file, 'r') as f: depot_reader = csv.DictReader(f) for row in depot_reader: vehicle = Vehicle() vehicle.depot_id = row['depot_id'] vehicle.x_coord = float(row['x_coord']) vehicle.y_coord = float(row['y_coord']) vehicle.type = row['vehicle_type'] vehicle.capacity=float(row['vehicle_capacity']) vehicle.free_speed=float(row['vehicle_speed']) vehicle.numbers=float(row['number_of_vehicle']) vehicle.fixed_cost=float(row['fixed_cost']) vehicle.variable_cost=float(row['variable_cost']) vehicle.start_time=float(row['start_time']) vehicle.end_time=float(row['end_time']) model.vehicle_dict[vehicle.type] = vehicle model.vehicle_type_list.append(vehicle.type)

def readCSVFile(demand_file, depot_file, model): model['demand_dict'] = {int(row['id']): Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['...

降低这段代码重复率：def readCSVFile(demand_file,depot_file,model): with open(demand_file,'r') as f: demand_reader=csv.DictReader(f) for row in demand_reader: demand = Demand() demand.id = int(row['id']) demand.x_coord = float(row['x_coord']) demand.y_coord = float(row['y_coord']) demand.demand = float(row['demand']) demand.start_time=float(row['start_time']) demand.end_time=float(row['end_time']) demand.service_time=float(row['service_time']) model.demand_dict[demand.id] = demand model.demand_id_list.append(demand.id) model.number_of_demands=len(model.demand_id_list) with open(depot_file, 'r') as f: depot_reader = csv.DictReader(f) for row in depot_reader: vehicle = Vehicle() vehicle.depot_id = row['depot_id'] vehicle.x_coord = float(row['x_coord']) vehicle.y_coord = float(row['y_coord']) vehicle.type = row['vehicle_type'] vehicle.capacity=float(row['vehicle_capacity']) vehicle.free_speed=float(row['vehicle_speed']) vehicle.numbers=float(row['number_of_vehicle']) vehicle.fixed_cost=float(row['fixed_cost']) vehicle.variable_cost=float(row['variable_cost']) vehicle.start_time=float(row['start_time']) vehicle.end_time=float(row['end_time']) model.vehicle_dict[vehicle.type] = vehicle model.vehicle_type_list.append(vehicle.type)

def readCSV(csv_file, model, obj_type): with open(csv_file, 'r') as f: csv_reader = csv.DictReader(f) for row in csv_reader: obj = obj_type() for key, value in row.items(): setattr(obj, key, ...

优化这段代码：降低这段代码重复率：def readCSVFile(demand_file, depot_file, model): model['demand_dict'] = {int(row['id']): Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['demand']), start_time=float(row['start_time']), end_time=float(row['end_time']), service_time=float(row['service_time'])) for row in csv.DictReader(open(demand_file))} model['demand_id_list'] = list(model['demand_dict'].keys()) model['number_of_demands'] = len(model['demand_id_list']) model['vehicle_dict'] = {row['vehicle_type']: Vehicle(depot_id=row['depot_id'], x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), type=row['vehicle_type'], capacity=float(row['vehicle_capacity']), free_speed=float(row['vehicle_speed']), numbers=float(row['number_of_vehicle']), fixed_cost=float(row['fixed_cost']), variable_cost=float(row['variable_cost']), start_time=float(row['start_time']), end_time=float(row['end_time'])) for row in csv.DictReader(open(depot_file))} model['vehicle_type_list'] = list(model['vehicle_dict'].keys())

demand_dict = {int(row['id']): parse_demand_row(row) for row in csv.DictReader(open(demand_file))} demand_id_list = list(demand_dict.keys()) number_of_demands = len(demand_id_list) vehicle_dict = {row...

优化这段代码：def run(demand_file,depot_file,epochs,pc,pm,popsize,n_select,opt_type): model=Model() model.pc=pc model.pm=pm model.popsize=popsize model.n_select=n_select model.opt_type=opt_type readCSVFile(demand_file,depot_file,model) calDistanceMatrix(model) generateInitialSol(model) history_best_obj = [] best_sol=Sol() best_sol.obj=float('inf') model.best_sol=best_sol start_time=time.time() for ep in range(epochs): ''' 计算适应度''' calFitness(model) ''' 选择''' selectSol(model) ''' 交叉''' crossSol(model) ''' 变异''' muSol(model) ''' 记录最优目标''' history_best_obj.append(model.best_sol.obj) print("迭代次数: %s，最优目标值: %s，运行时间: %s" % (ep+1,model.best_sol.obj,time.time()-start_time)) plotObj(history_best_obj) plotRoutes(model) outPut(model)

readCSVFile(demand_file, depot_file, model) calDistanceMatrix(model) generateInitialSol(model) best_sol = Sol() best_sol.obj = float('inf') model.best_sol = best_sol def train(model, epochs): ...

降低这段代码重复率：def readCSVFile(demand_file, depot_file, model): model['demand_dict'] = {int(row['id']): Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['demand']), start_time=float(row['start_time']), end_time=float(row['end_time']), service_time=float(row['service_time'])) for row in csv.DictReader(open(demand_file))} model['demand_id_list'] = list(model['demand_dict'].keys()) model['number_of_demands'] = len(model['demand_id_list']) model['vehicle_dict'] = {row['vehicle_type']: Vehicle(depot_id=row['depot_id'], x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), type=row['vehicle_type'], capacity=float(row['vehicle_capacity']), free_speed=float(row['vehicle_speed']), numbers=float(row['number_of_vehicle']), fixed_cost=float(row['fixed_cost']), variable_cost=float(row['variable_cost']), start_time=float(row['start_time']), end_time=float(row['end_time'])) for row in csv.DictReader(open(depot_file))} model['vehicle_type_list'] = list(model['vehicle_dict'].keys())

with open(file_path) as f: return {key_fn(row): value_fn(row) for row in csv.DictReader(f)} 然后就可以用这个函数来读取需求和车辆的字典了，代码如下： model['demand_dict'] = readDictFromFile...

降低这段代码的重复率：def run(demand_file,depot_file,epochs,pc,pm,popsize,n_select,opt_type): model=Model() model.pc=pc model.pm=pm model.popsize=popsize model.n_select=n_select model.opt_type=opt_type readCSVFile(demand_file,depot_file,model) calDistanceMatrix(model) generateInitialSol(model) history_best_obj = [] best_sol=Sol() best_sol.obj=float('inf') model.best_sol=best_sol start_time=time.time() for ep in range(epochs): ''' 计算适应度''' calFitness(model) ''' 选择''' selectSol(model) ''' 交叉''' crossSol(model) ''' 变异''' muSol(model) ''' 记录最优目标''' history_best_obj.append(model.best_sol.obj) print("迭代次数: %s，最优目标值: %s，运行时间: %s" % (ep+1,model.best_sol.obj,time.time()-start_time)) plotObj(history_best_obj) plotRoutes(model) outPut(model)

可以将一些重复的代码抽象成函数或方法，例如： ... readCSVFile(demand_file, depot_file, model) calDistanceMatrix(model) def selectSol(model): ... def crossSol(model): ... def muSol(model): ...

翻译：class Vehicle(): def init(self): self.depot_id=0 self.x_coord=0 self.y_coord=0 self.type=0 self.capacity=0 self.free_speed=1 self.fixed_cost=1.0 self.variable_cost=1.0 self.numbers=0 self.start_time=0 self.end_time=1440

这段代码定义了一个类 Vehicle，并且在初始化函数 __init__() 中定义了该类的属性，包括 depot_id、x_coord、y_coord、type、capacity、free_speed、fixed_cost、variable_cost、numbers、...

def generateOwnCarRoute(service_time, model, sol): pickup_node = copy.deepcopy(model.demand_id_list[0: 16]) own_pickup_node = [] own_delivery_node = [] route = [] sol.route_list = [] depot = model.depot_dict['d1'] vehicle_number = depot.depot_capacity departure = 0 arrival = 0 for i in pickup_node: if i not in model.crowd_pickup_node: own_pickup_node.append(i) own_delivery_node.append(i+16) while vehicle_number > 0 and len(own_pickup_node) > 0: route.append(depot.depot_id) minIndex = np.argmin([model.distance_matrix[depot.depot_id, own_pickup_node[i]] for i in range(0, len(own_pickup_node))]) minnode = own_pickup_node[minIndex] route.append(minnode) arrival = model.time_matrix[depot.depot_id, minnode] departure = arrival + service_time route.append(own_delivery_node[minIndex]) arrival = departure + model.time_matrix[minnode, own_delivery_node[minIndex]] departure += arrival + service_time last_node = own_delivery_node[minIndex] own_pickup_node.remove(minnode) own_delivery_node.remove(own_delivery_node[minIndex]) for j in own_pickup_node: next_minIndex = np.argmin([model.distance_matrix[last_node, j]]) next_minnode = own_pickup_node[next_minIndex] arrival = departure + model.time_matrix[last_node, next_minnode] if arrival <= model.demand_dict[next_minnode].end_time and arrival <= depot.dend_time: route.append(next_minnode) departure = arrival + service_time route.append(own_delivery_node[next_minIndex]) arrival = departure + model.time_matrix[next_minnode, own_delivery_node[next_minIndex]] departure += arrival + service_time last_node = own_delivery_node[next_minIndex] own_pickup_node.remove(next_minnode) own_delivery_node.remove(own_delivery_node[next_minIndex]) else: continue route.append(depot.depot_id) sol.route_list.append(route) vehicle_number = vehicle_number - 1 route = [] print(sol.route_list) return sol.route_list 这段代码的问题是有可能vehicle_number为0了，但是owner_pickup_node的长度还不为0，这种情况怎么解决

while vehicle_number > 0 and len(own_pickup_node) > 0 and len(sol.route_list) < model.depot_dict['d1'].depot_capacity: 这样，当所有车辆都被分配任务后，循环就会停止，避免了程序陷入无限循环的情况。

Traceback (most recent call last): File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 523, in <module> main(demand_file=demand_file, depot_file=depot_file, epochs=250, v_cap=3) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 503, in main sol3, route_list3 = local_search_two(crowd_route_list1, route_list2, sol, model, node) TypeError: cannot unpack non-iterable NoneType object

这个错误通常出现在你试图对一个 NoneType 对象进行解包操作的时候。在这个具体的错误中，是因为 local_search_two 函数返回了 None，导致解包时出现了这个错误。请检查 local_search_two 函数的实现，确保其...

def calCrowdcarCost(crowd_route_list, model): cost_of_distance = 0 crowd_wait_time = 0 model.crowdcarcost = 0 for route in crowd_route_list: timetable = [] for i in range(len(route)): if i == 0: depot_id = route[i] next_node_id = route[i+1] cost_of_distance = model.distance_matrix[depot_id, next_node_id] travel_time = int(model.distance_matrix[depot_id, next_node_id]) departure = max(0, model.demand_dict[next_node_id].start_time - travel_time) if departure == 0: crowd_wait_time = travel_time - model.demand_dict[next_node_id].start_time timetable.append((departure, departure)) elif 1 <= i <= len(route)-2: last_node_id = route[i-1] current_node_id = route[i] current_node = model.demand_dict[current_node_id] travel_time = int(model.distance_matrix[last_node_id, current_node_id]) cost_of_distance += model.distance_matrix[last_node_id, current_node_id] arrival = max(timetable[-1][1]+travel_time, current_node.start_time) if arrival == timetable[-1][1]+travel_time: crowd_wait_time += timetable[-1][1]+travel_time - current_node.start_time else: break model.crowdcarcost += model.fixcost + model.percost * cost_of_distance return model.crowdcarcost, crowd_wait_time 在这一段代码中我想知道每个点的等待时间总和，等待时间等于到达这个的时间减去它的时间窗上限

在这段代码中，你已经计算了每个点的等待时间，它们被累加到了crowd_wait_time变量中。如果你想得到每个点的等待时间总和，可以在循环中添加一个变量来记录。以下是修改后的代码： python def calCrowdcarCost...

Traceback (most recent call last): File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 589, in <module> main(demand_file=demand_file, depot_file=depot_file, v_cap=3) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 551, in main res1 = local_search_one(crowd_route_list1, route_list1, sol, model, node) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 453, in local_search_one owncar_route.index(0, 'd1') TypeError: slice indices must be integers or have an index method

这个错误通常出现在使用列表的index()方法时参数不正确。...要解决这个问题，你需要检查代码中使用owncar_route.index()方法时传递的参数是否正确，确保它是一个整数或者实现了__index__方法的对象。

def checkTimeWindow(route, model, node): timetable = [] a = 0 node = Node() departure = 0 for i in range(len(route)): if i == 0: next_node_id = route[i + 1] travel_time = int(model.distance_matrix[model.depot_dict[route[i]].depot_id, next_node_id]) departure = max(0, model.demand_dict[next_node_id].start_time - travel_time) timetable.append((int(departure), int(departure))) elif 1 <= i <= len(route) - 2: last_node_id = route[i - 1] current_node_id = route[i] current_node = model.demand_dict[current_node_id] travel_time = int(model.distance_matrix[last_node_id, current_node_id]) arrival = max(timetable[-1][1] + travel_time, current_node.start_time) departure = arrival + current_node.service_time timetable.append((int(arrival), int(departure))) if departure > current_node.end_time: departure = float('inf') a = 1 else: last_node_id = route[i - 1] travel_time = int(model.distance_matrix[last_node_id, model.depot_dict[route[i]].depot_id]) departure = timetable[-1][1] + travel_time timetable.append((int(departure), int(departure))) if departure < node.dend_time: a = a + 0 else: a = a + 1 return a

这段代码看起来像是一个函数，函数名为checkTimeWindow，它有三个参数，分别是route，model和node。它的功能可能是检查给定路径中的时间窗口是否满足要求。在函数内部，它使用列表timetable来存储每个节点的到达和...

C:\Users\lmx\Anaconda3\python.exe C:/Users/lmx/PycharmProjects/pythonProject/1.py Traceback (most recent call last): File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 539, in <module> main(demand_file=demand_file, depot_file=depot_file, epochs=250, v_cap=3) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 503, in main res1 = local_search_one(crowd_route_list1, route_list1, sol, model, node) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 424, in local_search_one a1 = checkPriority(owncar_route) File "C:/Users/lmx/PycharmProjects/pythonProject/1.py", line 273, in checkPriority if route[i] <= 16: TypeError: '<=' not supported between instances of 'str' and 'int'

这个错误是因为你在对一个字符串和整数进行比较时使用了操作符，但这两种类型是不可比较的。你需要检查一下你的 route 这个列表中的元素类型是否正确。如果其中包含了字符串类型的元素，你需要将它们转换为...

while len(own_pickup_node) > 0: route = [depot.depot_id] for i in range(min(len(own_pickup_node), 2)): minIndex = np.argmin([model.distance_matrix[depot.depot_id, own_pickup_node[j]] for j in range(0, len(own_pickup_node))]) minnode = own_pickup_node[minIndex] route.append(minnode) arrival = model.time_matrix[depot.depot_id, minnode] departure = arrival + service_time route.append(own_delivery_node[minIndex]) arrival = departure + model.time_matrix[minnode, own_delivery_node[minIndex]] departure += arrival + service_time last_node = own_delivery_node[minIndex] own_pickup_node.remove(minnode) own_delivery_node.remove(own_delivery_node[minIndex]) for j in own_pickup_node: next_minIndex = np.argmin([model.distance_matrix[last_node, j]]) next_minnode = own_pickup_node[next_minIndex] arrival = departure + model.time_matrix[last_node, next_minnode] if arrival <= model.demand_dict[next_minnode].end_time and arrival <= depot.dend_time: route.append(next_minnode) departure = arrival + service_time route.append(own_delivery_node[next_minIndex]) arrival = departure + model.time_matrix[next_minnode, own_delivery_node[next_minIndex]] departure += arrival + service_time last_node = own_delivery_node[next_minIndex] own_pickup_node.remove(next_minnode) own_delivery_node.remove(own_delivery_node[next_minIndex]) else: continue route.append(depot.depot_id) sol.route_list.append(route) vehicle_number = vehicle_number - 1 if vehicle_number == 0: break

需要注意的是，这段代码中的距离矩阵、时间矩阵、时间窗口等信息都是由 model 对象提供的，而且这里采用了 NumPy 库中的 argmin 函数来查找距离最近的取货点。另外，这段代码中的 sol 对象则是一个 Solution 类的...

input_tours_for_drones = 20 len_input_tours_for_drones = 7 aoi = utility.build_random_aoi(width_area, height_area, n_target, n_depots, hovering_time=5, seed=seed) depots = aoi.depots depot_first_drone = depots[0] tours_first_drone=[build_random_tour(aoi,depot_first_drone,np.random.randint(len_input_tours_for_drones - 5,len_input_tours_for_drones + 5)) for i in range(input_tours_for_drones)] depot_second_drone = depots[1] tours_second_drone=[build_random_tour(aoi,depot_second_drone,np.random.randint(len_input_tours_for_drones-5, len_input_tours_for_drones + 5)) for i in range(input_tours_for_drones)] uavs_to_tours = {drones[0]: tours_first_drone, drones[1]: tours_second_drone model = TotalCoverageModel(aoi, uavs_to_tours, max_rounds, debug=False) model.build() model.optimize() mrs = model.solution assert mrs is not None, "optimal solution not found" print("TC-OPT covers", mrs.coverage_score(), "targets using", mrs.max_rounds, "rounds") mrs.plot("TC-OPT") # for big istances (over 200/300 points) remove this plot mrs.plot_cumulative_coverage_for_round("TC-OPT") 以上为用Gurobi求解最优解问题，请解释以上程序： depot_first_drone = depots[0] tours_first_drone=[build_random_tour(aoi,depot_first_drone,np.random.randint(len_input_tours_for_drones - 5,len_input_tours_for_drones + 5)) for i in range(input_tours_for_drones)] depot_second_drone = depots[1] tours_second_drone=[build_random_tour(aoi,depot_second_drone,np.random.randint(len_input_tours_for_drones-5, len_input_tours_for_drones + 5)) for i in range(input_tours_for_drones)] uavs_to_tours = {drones[0]: tours_first_drone, drones[1]: tours_second_drone是什么意思

8. 调用 model.optimize() 方法求解模型的最优解。 9. 将最优解保存在变量 mrs 中，并打印出覆盖目标点的数量和使用的最大回合数。 10. 最后通过调用 mrs.plot() 方法和 mrs.plot_cumulative_coverage_for_round()...

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