This is a multi-echelon inventory model and demonstrates the benefits of computing safety stock based on multi-echelon considerations rather than single-echelon calculations.The network is plant->stocking point-> Distributor-> Retailer. The mean demand of retailer is 100 and sd-30. Since the network has only one sp/one distributor/one retailer, the same demand propagates up (subject to inventory netting). You can do safety stock computations at distributor and SP based on the classical safety stock formula. Post that keep reducing the safety stock at the distributor and see if the service level is getting impacted. Do you think you can manage with SS less than what is given by the classical formula (applied at distributor and stocking point?)

Business Logistics Supply Chain

Little's Law has various applications in Supply Chain. One of the application is the impact of Transit Times on In Transit Stocks and Total Stocks. This example demonstrates the relationship and the trade-off.

Supply Chain Transportation Logistics

This model gives an insight in the Study Book sales of Bol.com. Bol.com provides, besides of the B2C online business model, selling new books from suppliers to their customers, also a C2C online business model. This gives a customer the opportunity to sell their own books to other customers of Bol.com via Bol.com's website, by simply filling in the ISBN of the book on their second hand book website. The consumer pays a (relatively small) fee to bol.com for each book sold successfully. The payment part is handled by Bol.com, but the shipment has to be done by the customer (seller) itself. This model gives an insight of this process.

Sales Second Hand Books Finance Logistics

We model the system consisting of three groups of agents interacting together: Senders of package, Receivers of package, and carriers.Initially all of them are randomly spread geographically.Then some Senders and Receivers randomly are willing to interact, and searching for the available carrier. All carriers have different radius of availability (suppose humans may walk maximum 6-10 km, car - 200-400 km, jet - over 10000). So the condition of deal is carrier containing receiver and sender within his radius of availability and  who is free now.Connections between inactive agents deteriorate with decay rate, after some time receiver and sender forget about each other and may form other connections in the system.All agents have possibility to churn, and it is higher if they don't have any connections (any interest in the system)

Logistics Agent Modeling Connections Churn Agent Geography Agent Interaction

Logistics Supply Chain Warehouse

This Insight models the spread of the H1N1 influenza assuming that once an individual has become infected, they are immune from reinfection.

H1N1 Epidemic Logistics

there is a distributed net of independent carriers interacting geographically to build continuous supply chain. We model the dynamics of the system, assuming scarcity of available agents, under the condition that the total path must be no longer then X defined economically.

Logistics

Logistics Transportation Packaging Meal Kits

Single Simple Systems Model for Logistics

Logistics Transportation Packaging Delivery

Little's Law has various applications in Supply Chain. One of the application is the impact of Transit Times on In Transit Stocks and Total Stocks. This example demonstrates the relationship and the trade-off.

Supply Chain Transportation Logistics

Logistics

We model the system consisting of three groups of agents interacting together: Senders of package, Receivers of package, and carriers.Initially all of them are randomly spread geographically.Then some Senders and Receivers randomly are willing to interact, and searching for the available carrier. All carriers have different radius of availability (suppose humans may walk maximum 6-10 km, car - 200-400 km, jet - over 10000). So the condition of deal is carrier containing receiver and sender within his radius of availability and  who is free now.Connections between inactive agents deteriorate with decay rate, after some time receiver and sender forget about each other and may form other connections in the system.All agents have possibility to churn, and it is higher if they don't have any connections (any interest in the system)

Logistics Agent Modeling Connections Churn Agent Geography Agent Interaction