modelInventoryForresterNormalNoise

Inventory simulation with random orders

Information

Customer Demand Modeled as Noise

Customer demand usually fluctuates in a random fashion. Therefore, it is modeled in this simulation as normally distributed random noise with a mean value of mean=1000 and a standard deviation of stdev=100. The noise is sampled once per week and kept constant for the corresponding week. The order flow is modeled using the equation:

RRR(t) = RRRini + normal(1000,100);


Simulate the model across 10 years (520 weeks), and plot on a single graph the incoming orders, the production flow in the factory, and the levels of goods in retail, distribution, and the factory as functions of time:

Choose Radau-IIa as your integration algorithm. It handles noise input better than DASSL.


Parameters

TypeNameDefaultDescription
RealRRRiniTop1000Inital value of customer requests at retail
RealRRDiniTopRRRiniTopInital value of requisitions received at distribution
RealRRFiniTopRRRiniTopInital value of requisitions received at factory

Components

TypeNameDefaultDescription
RealrandomNoiseRandom noise signal
RealfactoryFlowManufacturing flow at factory
RealretailStockStock of goods in retail
RealdistributionStockStock of goods in distribution
RealfactoryStockStock of goods in factory
FactoryFactory1
DistributionDistribution1
RetailRetail1
Utilities.NoiseNormalNoiseNormal1
BondLib.Sources.mSfmSf
BondLib.Bonds.eBondB1
BondLib.Sources.SeSe1