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发表于 2023-12-24 21:34:57
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根据需求分析,我们可以使用图的数据结构来构建“一带一路”地图,并实现相关功能。下面是一个简单的示例:
- import networkx as nx
- # 创建一个空的图对象
- G = nx.Graph()
- # 添加国家节点
- countries = ['中国', '哈萨克斯坦', '俄罗斯', '白俄罗斯', '波兰', '德国', '法国', '西班牙']
- for country in countries:
- G.add_node(country)
- # 添加班列边及其属性
- G.add_edge('中国', '哈萨克斯坦', distance=3000, time=5, capacity=1000, goods='工艺品、饮品、玩具')
- G.add_edge('哈萨克斯坦', '俄罗斯', distance=2000, time=3, capacity=800, goods='工艺品、饮品、玩具')
- G.add_edge('俄罗斯', '白俄罗斯', distance=500, time=1, capacity=600, goods='工艺品、饮品、玩具')
- G.add_edge('白俄罗斯', '波兰', distance=800, time=2, capacity=700, goods='工艺品、饮品、玩具')
- G.add_edge('波兰', '德国', distance=1000, time=2, capacity=900, goods='工艺品、饮品、玩具')
- G.add_edge('德国', '法国', distance=1000, time=2, capacity=800, goods='工艺品、饮品、玩具')
- G.add_edge('法国', '西班牙', distance=1500, time=4, capacity=1000, goods='工艺品、饮品、玩具')
- # 查询所有班列的相关信息
- for edge in G.edges():
- start, end = edge
- distance = G.edges[edge]['distance']
- time = G.edges[edge]['time']
- capacity = G.edges[edge]['capacity']
- goods = G.edges[edge]['goods']
- print(f'{start}到{end}:距离{distance}公里,耗时{time}天,载货量{capacity}吨,货物类型为{goods}')
- # 根据企业的货运需求推荐班列信息
- def recommend_routes(origin, destination, weight):
- routes = nx.all_simple_paths(G, origin, destination)
- recommended_route = None
- min_time = float('inf')
- min_cost = float('inf')
- for route in routes:
- total_time = 0
- total_cost = 0
- for i in range(len(route)-1):
- edge = (route[i], route[i+1])
- total_time += G.edges[edge]['time']
- total_cost += G.edges[edge]['distance'] * weight * 10 # 假设运费为每公里每吨10元
- if total_time < min_time:
- min_time = total_time
- min_cost = total_cost
- recommended_route = route
- elif total_time == min_time and total_cost < min_cost:
- min_cost = total_cost
- recommended_route = route
- return recommended_route, min_time, min_cost
- # 使用示例
- origin = '中国'
- destination = '西班牙'
- weight = 100
- route, time, cost = recommend_routes(origin, destination, weight)
- print(f'推荐路线:{route},总耗时{time}天,总费用{cost}元')
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这只是一个基本的代码示例,根据实际需求可以进一步完善和优化。希望能帮到你!
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