for drone in drones1: trajs1 = trajectories_builder.compute_trajectories(drone, depots[0]) out_trajectories1[drone] = trajs1, for drone in drones2: trajs2 = trajectories_builder.compute_trajectories(drone, depots[0]) out_trajectories2[drone] = trajs2, 如何修改程序能使得out_trajectories1[drone]和out_trajectories2[drone]的内容加到一起,通过out_trajectories[drone]输出

时间: 2024-01-01 17:06:55 浏览: 25
你在循环中判断 drone 属于哪个列表,并将轨迹信息累加到 out_trajectories[drone] 中,如下所示: ``` out_trajectories = {} for drone in drones1 + drones2: trajs = trajectories_builder.compute_trajectories(drone, depots[0]) if drone in drones1: if drone in out_trajectories1: out_trajectories[drone] = out_trajectories1[drone] + trajs else: out_trajectories[drone] = trajs else: if drone in out_trajectories2: out_trajectories[drone] = out_trajectories2[drone] + trajs else: out_trajectories[drone] = trajs print(out_trajectories[drone]) ``` 这样修改后,程序会将 out_trajectories1[drone] 和 out_trajectories2[drone] 的内容加到一起,并将结果存储到 out_trajectories[drone] 中。需要注意的是,如果某个 drone 在两个列表中都出现,需要将两个列表中对应的轨迹信息累加起来。

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class AbstractGreedyAndPrune(): def __init__(self, aoi: AoI, uavs_tours: dict, max_rounds: int, debug: bool = True): self.aoi = aoi self.max_rounds = max_rounds self.debug = debug self.graph = aoi.graph self.nnodes = self.aoi.n_targets self.uavs = list(uavs_tours.keys()) self.nuavs = len(self.uavs) self.uavs_tours = {i: uavs_tours[self.uavs[i]] for i in range(self.nuavs)} self.__check_depots() self.reachable_points = self.__reachable_points() def __pruning(self, mr_solution: MultiRoundSolution) -> MultiRoundSolution: return utility.pruning_multiroundsolution(mr_solution) def solution(self) -> MultiRoundSolution: mrs_builder = MultiRoundSolutionBuilder(self.aoi) for uav in self.uavs: mrs_builder.add_drone(uav) residual_ntours_to_assign = {i : self.max_rounds for i in range(self.nuavs)} tour_to_assign = self.max_rounds * self.nuavs visited_points = set() while not self.greedy_stop_condition(visited_points, tour_to_assign): itd_uav, ind_tour = self.local_optimal_choice(visited_points, residual_ntours_to_assign) residual_ntours_to_assign[itd_uav] -= 1 tour_to_assign -= 1 opt_tour = self.uavs_tours[itd_uav][ind_tour] visited_points |= set(opt_tour.targets_indexes) # update visited points mrs_builder.append_tour(self.uavs[itd_uav], opt_tour) return self.__pruning(mrs_builder.build()) class CumulativeGreedyCoverage(AbstractGreedyAndPrune): choice_dict = {} for ind_uav in range(self.nuavs): uav_residual_rounds = residual_ntours_to_assign[ind_uav] if uav_residual_rounds > 0: uav_tours = self.uavs_tours[ind_uav] for ind_tour in range(len(uav_tours)): tour = uav_tours[ind_tour] quality_tour = self.evaluate_tour(tour, uav_residual_rounds, visited_points) choice_dict[quality_tour] = (ind_uav, ind_tour) best_value = max(choice_dict, key=int) return choice_dict[best_value] def evaluate_tour(self, tour : Tour, round_count : int, visited_points : set): new_points = (set(tour.targets_indexes) - visited_points) return round_count * len(new_points) 如何改写上述程序,使其能返回所有已经探索过的目标点visited_points的数量,请用代码表示

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

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