diff options
| -rw-r--r-- | multiple_ant_colony_system.py | 25 | ||||
| -rw-r--r-- | vprtw_aco_figure.py | 6 |
2 files changed, 20 insertions, 11 deletions
diff --git a/multiple_ant_colony_system.py b/multiple_ant_colony_system.py index 3e9b0f3..0ef14da 100644 --- a/multiple_ant_colony_system.py +++ b/multiple_ant_colony_system.py @@ -8,10 +8,12 @@ from queue import Queue from concurrent.futures import ThreadPoolExecutor import copy import time +from multiprocessing import Process +from multiprocessing import Queue as MPQueue class MultipleAntColonySystem: - def __init__(self, graph: VrptwGraph, ants_num=10, beta=2, q0=0.1, whether_or_not_to_show_figure=True): + def __init__(self, graph: VrptwGraph, ants_num=10, beta=1, q0=0.1, whether_or_not_to_show_figure=True): super() # graph 结点的位置、服务时间信息 self.graph = graph @@ -173,6 +175,8 @@ class MultipleAntColonySystem: for thread in ants_thread: thread.result() + ant_best_travel_distance = None + ant_best_path = None # 判断蚂蚁找出来的路径是否是feasible的，并且比全局的路径要好 for ant in ants: @@ -188,14 +192,19 @@ class MultipleAntColonySystem: print('[acs_time]: receive global path info') global_best_path, global_best_distance, global_used_vehicle_num = info.get_path_info() - # 如果比全局的路径要好，则要将该路径发送到macs中 - if ant.index_to_visit_empty() and ant.total_travel_distance < global_best_distance: - print('[acs_time]: ant found a improved feasible path, send path info to macs') - path_found_queue.put(PathMessage(ant.travel_path, ant.total_travel_distance)) + # 路径蚂蚁计算得到的最短路径 + if ant.index_to_visit_empty() and (ant_best_travel_distance is None or ant.total_travel_distance < ant_best_travel_distance): + ant_best_travel_distance = ant.total_travel_distance + ant_best_path = ant.travel_path # 在这里执行信息素的全局更新 new_graph.global_update_pheromone(global_best_path, global_best_distance) + # 向macs发送计算得到的当前的最佳路径 + if ant_best_travel_distance is not None and ant_best_travel_distance < global_best_distance: + print('[acs_time]: local search for global_path found a improved feasible path, send path info to macs') + path_found_queue.put(PathMessage(ant_best_path, ant_best_travel_distance)) + ants_thread.clear() for ant in ants: ant.clear() @@ -297,8 +306,8 @@ class MultipleAntColonySystem: 开启另外的线程来跑multiple_ant_colony_system， 使用主线程来绘图 :return: """ - path_queue_for_figure = Queue() - multiple_ant_colony_system_thread = Thread(target=self._multiple_ant_colony_system, args=(path_queue_for_figure,)) + path_queue_for_figure = MPQueue() + multiple_ant_colony_system_thread = Process(target=self._multiple_ant_colony_system, args=(path_queue_for_figure,)) multiple_ant_colony_system_thread.start() # 是否要展示figure @@ -311,7 +320,7 @@ class MultipleAntColonySystem: if self.whether_or_not_to_show_figure: path_queue_for_figure.put(PathMessage(None, None)) - def _multiple_ant_colony_system(self, path_queue_for_figure: Queue): + def _multiple_ant_colony_system(self, path_queue_for_figure: MPQueue): """ 调用acs_time 和 acs_vehicle进行路径的探索 :param path_queue_for_figure: diff --git a/vprtw_aco_figure.py b/vprtw_aco_figure.py index 79fab72..98efe80 100644 --- a/vprtw_aco_figure.py +++ b/vprtw_aco_figure.py @@ -1,9 +1,9 @@ import matplotlib.pyplot as plt -from queue import Queue +from multiprocessing import Queue as MPQueue class VrptwAcoFigure: - def __init__(self, nodes: list, path_queue: Queue): + def __init__(self, nodes: list, path_queue: MPQueue): """ matplotlib绘图计算需要放在主线程，寻找路径的工作建议另外开一个线程， 当寻找路径的线程找到一个新的path的时候，将path放在path_queue中，图形绘制线程就会自动进行绘制 @@ -71,4 +71,4 @@ class VrptwAcoFigure: x_list = [self.nodes[path[i - 1]].x, self.nodes[path[i]].x] y_list = [self.nodes[path[i - 1]].y, self.nodes[path[i]].y] self.figure_ax.plot(x_list, y_list, color=self._line_color, linewidth=1.5, label='line') - plt.pause(0.02) + plt.pause(0.2) |