摘要: import numpy as np matches = np.array([ [0, 1, 0, 1, 1, 1], # 1队 [0, 0, 0, 1, 1, 1], # 2队 [1, 1, 0, 1, 0, 0], # 3队 [0, 0, 0, 0, 1, 1], # 4队 [0, 0, 1, 阅读全文
posted @ 2024-10-27 21:32 唐锦珅 阅读(21) 评论(0) 推荐(0)
摘要: import numpy as np distances = np.array([ [0, 2, 7, np.inf, np.inf, np.inf], [2, 0, 4, 6, 8, np.inf], [7, 4, 0, 1, 3, np.inf], [np.inf, 6, 1, 0, 1, 6] 阅读全文
posted @ 2024-10-27 21:31 唐锦珅 阅读(10) 评论(0) 推荐(0)
摘要: initial_costs = [2.5, 2.6, 2.8, 3.1] salvage_values = [2.0, 1.6, 1.3, 1.1] maintenance_costs = [0.3, 0.8, 1.5, 2.0] dp = [[float('inf')] * 2 for _ in 阅读全文
posted @ 2024-10-27 21:30 唐锦珅 阅读(15) 评论(0) 推荐(0)
摘要: import heapq def prim(graph, start): num_nodes = len(graph) visited = [False] * num_nodes min_heap = [(0, start, -1)] mst_cost = 0 mst_edges = [] whil 阅读全文
posted @ 2024-10-27 21:30 唐锦珅 阅读(10) 评论(0) 推荐(0)
摘要: edges = [ ("Pe", "T", 13), ("Pe", "N", 68), ("Pe", "M", 78), ("Pe", "L", 51), ("Pe", "Pa", 51), ("T", "N", 68), ("T", "M", 70), ("T", "L", 6 阅读全文
posted @ 2024-10-27 21:29 唐锦珅 阅读(17) 评论(0) 推荐(0)
摘要: import networkx as nx import matplotlib.pyplot as plt G = nx.Graph() nodes = ['v1', 'v2', 'v3', 'v4', 'v5', 'v6'] G.add_nodes_from(nodes) edges = [ (' 阅读全文
posted @ 2024-10-27 21:28 唐锦珅 阅读(9) 评论(0) 推荐(0)
摘要: MAX_A = 15 MAX_B = 24 MAX_DEBUG = 5 products = [ {"name": "Ⅰ", "A_hours": 1, "B_hours": 6, "debug_hours": 1, "profit": 2}, # 假设产品Ⅰ至少使用1小时设备A {"name": 阅读全文
posted @ 2024-10-27 21:26 唐锦珅 阅读(23) 评论(0) 推荐(0)
摘要: import matplotlib.pyplot as plt import numpy as np import cvxpy as cp x=cp.Variable(6,pos=True) obj=cp.Minimize(x[5]) a1=np.array([0.025, 0.015, 0.055 阅读全文
posted @ 2024-10-27 21:25 唐锦珅 阅读(20) 评论(0) 推荐(0)
摘要: import numpy as np def f(x): return (abs(x + 1) - abs(x - 1)) / 2 + np.sin(x) def g(x): return (abs(x + 3) - abs(x - 3)) / 2 + np.cos(x) 假设我们有一些初始猜测值( 阅读全文
posted @ 2024-10-27 21:18 唐锦珅 阅读(11) 评论(0) 推荐(0)
摘要: import numpy as np from scipy.linalg import eig 定义矩阵 A = np.array([[-1, 1, 0], [-4, 3, 0], [1, 0, 2]]) 计算特征值和特征向量 eigenvalues, eigenvectors = eig(A) 打 阅读全文
posted @ 2024-10-27 21:17 唐锦珅 阅读(17) 评论(0) 推荐(0)