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)

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...

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)

def readCSVFile(demand_file, depot_file, model): # 读取需求数据 demand_df = pd.read_csv(demand_file) demand_df = demand_df.apply(lambda row: Demand( id=int(row['id']), x_coord=float(row['x_coord'...

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)

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, float(value) if value.replace('.', '', 1)....

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、...

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 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 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。根据错误提示，你传递给了owncar_route.index()方法的参数是(0, 'd1')，这个参数是一个元组，其中包含两个元素，第一个元素是0，第二个元素是字符串'd1'...

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...

/depot_tools/.cipd_bin/vpython3: 没有那个文件或目录

如果您确定这个路径是正确的，那么可能是由于权限问题或其他系统错误导致无法找到这个文件或目录。您可以尝试检查并修正路径中可能存在的拼写错误，并确认文件/目录是否存在于系统中。另外，您也可以尝试使用管理员...

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...

depot_tools/

depot_tools是一组用于Chromium开发和其他相关项目的工具集合。它包含一组用于管理代码库、运行测试以及构建和打包代码的脚本。它还提供了许多用于Chromium开发的有用工具，例如Chromium的代码审核工具（codereview...

depot_tool

Depot Tools 是一组由 Google 开发的开源命令行工具，主要用于管理和自动化 Chrome 和 Chromium 开发过程中的依赖和构建流程。它们主要针对的是那些贡献者和开发者，提供了一种便捷的方式来下载和更新项目代码，编译...

相关推荐

depot_tools工具包

depot_tools_2017.3.24（禁止cipd更新）

depot_tools

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

/depot_tools/.cipd_bin/vpython3: 没有那个文件或目录

depot_tools/

depot_tool

最新推荐

webrtc_Linux源代码获取以及编译

webrtc_android源代码获取以及编译

webrtc_IOS编译

中式汉堡市场调研报告：2023年市场规模约为1890亿元

GitHub图片浏览插件：直观展示代码中的图像

管理建模和仿真的文件

【OPPO手机故障诊断专家】：工程指令快速定位与解决

求[100，900]之间相差为12的素数对（注：要求素数对的两个素数均在该范围内）的个数

Android IPTV项目：直播频道的实时流媒体实现

"互动学习：行动中的多样性与论文攻读经历"

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