物流与运输
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2 min read458 words

物流与运输

把正确的货物在正确的时间送到正确的地方——物流决定了供应链的最终效率。

物流网络

graph TD PLANT[工厂] --> CDC[中央配送中心] CDC --> RDC1[区域仓-华东] CDC --> RDC2[区域仓-华南] CDC --> RDC3[区域仓-华北] RDC1 --> LD1[末端配送] RDC2 --> LD2[末端配送] RDC3 --> LD3[末端配送] LD1 --> CUST[客户] LD2 --> CUST LD3 --> CUST style CDC fill:#e3f2fd,stroke:#1565c0,stroke-width:2px style CUST fill:#c8e6c9,stroke:#388e3c,stroke-width:2px

运输方式对比

方式 速度 成本/kg 载量 适合
公路 中 ¥0.3-1.5 1-30吨 国内中短距
铁路 中 ¥0.1-0.5 50-5000吨 大宗/长距
海运 慢 ¥0.02-0.1 万吨级 跨境大宗
空运 快 ¥15-50 <100吨 高价值/紧急
快递 快 ¥3-20 <30kg 电商小件

TMS 运输管理

"""
TMS 运输管理
"""
from dataclasses import dataclass
@dataclass
class Shipment:
id: str
origin: str
destination: str
weight_kg: float
volume_cbm: float
urgency: str  # normal / express / critical
class TransportManager:
"""运输管理器"""
# 运费费率 (元/kg)
RATES = {
"公路": {"normal": 0.5, "express": 1.0, "critical": 2.0},
"铁路": {"normal": 0.15, "express": 0.3, "critical": 0.5},
"空运": {"normal": 20, "express": 30, "critical": 45},
}
@classmethod
def select_mode(cls, shipment: Shipment) -> dict:
"""运输方式选择"""
recommendations = []
for mode, rates in cls.RATES.items():
rate = rates[shipment.urgency]
cost = shipment.weight_kg * rate
recommendations.append({
"方式": mode,
"费率": f"¥{rate}/kg",
"总费用": f"¥{cost:,.0f}",
})
recommendations.sort(
key=lambda x: float(x["总费用"][1:].replace(",", ""))
)
return {
"货物": shipment.id,
"重量": f"{shipment.weight_kg}kg",
"紧急度": shipment.urgency,
"方案对比": recommendations,
"推荐": recommendations[0]["方式"],
}
@staticmethod
def consolidation(
shipments: list[Shipment],
) -> dict:
"""货物合并"""
total_weight = sum(s.weight_kg for s in shipments)
total_volume = sum(s.volume_cbm for s in shipments)
# 整车 vs 零担
if total_weight >= 5000:
mode = "整车 (FTL) — 独占车辆更划算"
elif total_weight >= 500:
mode = "零担 (LTL) — 与其他货物共享"
else:
mode = "快递/小包"
return {
"合并货物数": len(shipments),
"总重量": f"{total_weight:,.0f} kg",
"总体积": f"{total_volume:.1f} CBM",
"建议方式": mode,
}
tm = TransportManager()
# 单票选择
s1 = Shipment("SH-001", "深圳", "上海", 800, 2.5, "express")
result = tm.select_mode(s1)
print(f"=== {result['货物']} ({result['重量']}, {result['紧急度']}) ===")
for r in result["方案对比"]:
print(f"  {r['方式']}: {r['总费用']}")
print(f"  推荐: {result['推荐']}")
# 合并运输
shipments = [
Shipment("SH-001", "深圳", "上海", 800, 2.5, "normal"),
Shipment("SH-002", "深圳", "上海", 1200, 3.0, "normal"),
Shipment("SH-003", "深圳", "上海", 500, 1.5, "normal"),
]
print("\n=== 货物合并 ===")
for k, v in tm.consolidation(shipments).items():
print(f"  {k}: {v}")

运输优化策略

策略 方法 节省
路线优化 TSP/VRP 算法 10-20%
货物合并 LTL → FTL 15-30%
多式联运 铁路+公路组合 20-40%
回程利用 空车返程拉货 30-50%
区域集配 城市配送中心集中分拣 10-25%

最后一公里

方案 成本/件 覆盖 体验
快递到门 ¥3-8 全覆盖 最佳
驿站自提 ¥1-3 城市 中
智能柜 ¥0.3-0.5 社区 中
无人车/无人机 ¥1-5 试点 新颖

行动清单

下一节：02-跨境物流与清关 — 跨境物流与清关实战指南。