Python3实现单级库存仿真，single echelon inventory assessment

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参考代码的来源：
https://github.com/anshul-musing/single-echelon-inventory-assessment/blob/master/src/simpy_3.0/simLostSales.py

src/simpy_3.0/simBackorder.py

这段代码主要模拟单级供应链，所考虑的库存参数为在途库存、库存水平、服务水平。
假设这个系统采用的是“一旦库存水平低于再订货点（固定），管理者立即下订单（固定）”的订货策略。
假设当前未被满足的订单允许被后期的补货满足，
基于订单有多晚被满足 ，计算服务水平。
假设需求服从正态分布、提前期服从均匀分布。

"""This module simulates a single-echelon supply chain
and calculates inventory profile (along with associated inventory
parameters such as on-hand, inventory position, service level, etc.)
across timeThe system follows a reorder point-reorder quantity policy
If inventory position <= ROP, an order of a fixed reorder
quantity (ROQ) is placed by the facilityIt is assumed that any unfulfilled order is backordered
and is fulfilled whenever the material is available in the
inventory.  The service level is estimated based on how
late the order was fulfilledDemand is assumed to be Normally distributed
Lead time is assumed to follow a uniform distribution
"""__author__ = 'Anshul Agarwal'import simpy
import numpy as np# Stocking facility class
class stockingFacility(object): ## ?? why we need to in herit 'object'?# initialize the new facility objectdef __init__(self, env, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime):self.env = envself.on_hand_inventory = initialInvself.inventory_position = initialInvself.ROP = ROP # inventory positionself.ROQ = ROQ # fixed order quantityself.meanDemand = meanDemandself.demandStdDev = demandStdDevself.minLeadTime = minLeadTimeself.maxLeadTime = maxLeadTimeself.totalDemand = 0.0self.totalBackOrder = 0.0self.totalLateSales = 0.0self.serviceLevel = 0.0env.process(self.runOperation())# main subroutine for facility operation# it records all stocking metrics for the facilitydef runOperation(self):while True:yield self.env.timeout(1.0)# demand newly generateddemand = float(np.random.normal(self.meanDemand, self.demandStdDev, 1))self.totalDemand += demand# shipment 是该仓库送出的量，而self.ROQ是该仓库的补货量shipment = min(demand + self.totalBackOrder, self.on_hand_inventory) # the amount of goods available to sendself.on_hand_inventory -= shipment # send the shipment to some retailerself.inventory_position -= shipmentbackorder = demand - shipment # the amount of demand unmet temporarilyself.totalBackOrder += backorderself.totalLateSales += max(0.0, backorder)# if the current inventory position is less than ROP, then place an orderif self.inventory_position <= 1.01 * self.ROP:  # multiply by 1.01 to avoid rounding issuesself.env.process(self.ship(self.ROQ))# why we revise 'self.on_hand_inv' in the method 'ship', and revise 'self.inv_position' outside 'ship'self.inventory_position += self.ROQ# subroutine for a new order placed by the facilitydef ship(self, orderQty):# recall that we assume the lead time follows an uniform distributionleadTime = int(np.random.uniform(self.minLeadTime, self.maxLeadTime, 1))yield self.env.timeout(leadTime)  # wait for the lead time before delivering# now 'orderQty' goods is receivedself.on_hand_inventory += orderQty# Simulation module
def simulateNetwork(seedinit, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime):env = simpy.Environment()  # initialize SimPy simulation instancenp.random.seed(seedinit)s = stockingFacility(env, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime)env.run(until=365)  # simulate for 1 years.serviceLevel = 1 - s.totalLateSales / s.totalDemand # 服务水平的定义：那些被及时满足的需求的占比return s######## Main statements to call simulation ########
meanDemand = 500.0
demandStdDev = 100.0
minLeadTime = 7
maxLeadTime = 13
CS = 5000.0
ROQ = 6000.0
ROP = max(CS,ROQ)
initialInv = ROP + ROQ# Simulate
replications = 100
sL = []
for i in range(replications):nodes = simulateNetwork(i,initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime)sL.append(nodes.serviceLevel)sLevel = np.array(sL)
print("Avg. service level: " + str(np.mean(sLevel)))
print("Service level standard deviation: " + str(np.std(sLevel)))

src/simpy_3.0/simLostSales.py

不同于上一小节的地方在于，这里不允许回购，而是允许发生销售损失（lost sales）。
因此，在代码实现方面也会有微妙的差别，具体如下，

1. 在类stockingFacility中数据self.totalShipped用于记录从这个仓库发出了多少货；
2. 在类stockingFacility的方法runOperation中，当前从该仓库的送出量shipment的计算方式不再考虑backorder；
3. 在函数simulateNetwork中，计算服务水平（从该仓库的送出量占总需求量的比例）。

"""This module simulates a single-echelon supply chain
and calculates inventory profile (along with associated inventory
parameters such as on-hand, inventory position, service level, etc.)
across timeThe system follows a reorder point-reorder quantity policy
If inventory position <= ROP, an order of a fixed reorder
quantity (ROQ) is placed by the facilityIt is assumed that any unfulfilled order is lost
The service level is estimated based on how much
of the demand was fulfilledDemand is assumed to be Normally distributed
Lead time is assumed to follow a uniform distribution
"""__author__ = 'Anshul Agarwal'import simpy
import numpy as np# Stocking facility class
class stockingFacility(object):# initialize the new facility objectdef __init__(self, env, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime):self.env = envself.on_hand_inventory = initialInvself.inventory_position = initialInvself.ROP = ROPself.ROQ = ROQself.meanDemand = meanDemandself.demandStdDev = demandStdDevself.minLeadTime = minLeadTimeself.maxLeadTime = maxLeadTimeself.totalDemand = 0.0self.totalShipped = 0.0 # !!self.serviceLevel = 0.0env.process(self.runOperation())# main subroutine for facility operation# it records all stocking metrics for the facilitydef runOperation(self):while True:yield self.env.timeout(1.0)demand = float(np.random.normal(self.meanDemand, self.demandStdDev, 1))self.totalDemand += demandshipment = min(demand, self.on_hand_inventory) # !!self.totalShipped += shipmentself.on_hand_inventory -= shipmentself.inventory_position -= shipmentif self.inventory_position <= 1.01 * self.ROP:  # multiply by 1.01 to avoid rounding issuesself.env.process(self.ship(self.ROQ))self.inventory_position += self.ROQ# subroutine for a new order placed by the facilitydef ship(self, orderQty):leadTime = int(np.random.uniform(self.minLeadTime, self.maxLeadTime, 1))yield self.env.timeout(leadTime)  # wait for the lead time before deliveringself.on_hand_inventory += orderQty# Simulation module
def simulateNetwork(seedinit, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime):env = simpy.Environment()  # initialize SimPy simulation instancenp.random.seed(seedinit)s = stockingFacility(env, initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime)env.run(until=365)  # simulate for 1 years.serviceLevel = s.totalShipped / s.totalDemand # !!return s######## Main statements to call simulation ########
meanDemand = 500.0
demandStdDev = 100.0
minLeadTime = 7
maxLeadTime = 13
CS = 5000.0
ROQ = 6000.0
ROP = max(CS,ROQ)
initialInv = ROP + ROQ# Simulate
replications = 100
sL = []
for i in range(replications):nodes = simulateNetwork(i,initialInv, ROP, ROQ, meanDemand, demandStdDev, minLeadTime, maxLeadTime)sL.append(nodes.serviceLevel)sLevel = np.array(sL)
print("Avg. service level: " + str(np.mean(sLevel)))
print("Service level standard deviation: " + str(np.std(sLevel)))

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