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工具包

depot_tools工具包 https://commondatastorage.googleapis.com/chrome-infra-docs/flat/depot_tools/docs/html/depot_tools_tutorial.html#_setting_up

depot_tools工具 — Linux/Mac版本

depot_tools

depot_tools 工具最新refs_heads_main 主分支代码

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：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): ...

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...

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 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...

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。...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。

下载depot_tools

depot_tools是一组Google开发的工具集，用于帮助开发者下载和管理大型项目的源代码。要下载depot_tools，首先需要安装Git和Python环境。接下来，可以通过Git克隆depot_tools仓库并添加路径到系统环境变量中。在...

安装depot_tools

以下是安装depot_tools的步骤： 1.下载depot_tools.zip文件并解压缩到某个目录下，例如/home/user/depot_tools。 2.将depot_tools目录添加到环境变量中。可以通过在.bashrc文件中添加以下行来实现： shell ...

相关推荐

depot_tools工具包

depot_tools工具 — Linux/Mac版本

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

下载depot_tools

安装depot_tools

最新推荐

2107381120 王孟丽 实验2 (1).docx

zigbee-cluster-library-specification

管理建模和仿真的文件

实现实时数据湖架构：Kafka与Hive集成

可见光定位LED及其供电硬件具体型号，广角镜头和探测器，实验设计具体流程步骤，

JSBSim Reference Manual

"互动学习：行动中的多样性与论文攻读经历"

实现实时监控告警系统：Kafka与Grafana整合

解释这行代码 c = ((double)rand() / RAND_MAX) * (a + b - fabs(a - b)) + fabs(a - b);

c++校园超市商品信息管理系统课程设计说明书(含源代码) (2).pdf

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

2107381120 王孟丽实验2 (1).docx