How can you incorporate demand forecasting into OR problem formulations for supply chain logistics?

1 Network design

Network design is the OR problem of determining the optimal location and capacity of facilities, such as warehouses, factories, and distribution centers, in a supply chain network. It also involves deciding how to allocate products and services among the facilities, and how to route the transportation flows between them. Network design aims to minimize the total cost of the supply chain, while meeting the demand and service level requirements of the customers. Demand forecasting can help you to incorporate the expected demand patterns, growth rates, and seasonality into your network design model. For example, you can use demand forecasting to estimate the future demand for each product and customer segment, and then use these estimates as inputs for your network design model. This way, you can design a network that can adapt to the changing demand conditions, and avoid over- or under-capacity issues.

2 Inventory management

Inventory management is the OR problem of determining the optimal quantity and timing of ordering and holding products in a supply chain. It also involves deciding how to allocate inventory among different locations, and how to handle inventory shortages or surpluses. Inventory management aims to balance the trade-off between inventory costs, such as ordering, holding, and shortage costs, and customer service levels, such as fill rates and lead times. Demand forecasting can help you to incorporate the demand uncertainty and variability into your inventory management model. For example, you can use demand forecasting to estimate the probability distribution of the demand for each product and location, and then use these estimates as inputs for your inventory management model. This way, you can determine the optimal inventory policies that can minimize the inventory costs, while meeting the customer service levels.

3 Vehicle routing

Vehicle routing is the OR problem of determining the optimal routes and schedules for a fleet of vehicles that deliver products or services to a set of customers in a supply chain. It also involves deciding how to assign vehicles to customers, and how to load and unload the products or services. Vehicle routing aims to minimize the total travel time, distance, or cost of the fleet, while meeting the demand and time window constraints of the customers. Demand forecasting can help you to incorporate the demand variability and dynamics into your vehicle routing model. For example, you can use demand forecasting to estimate the expected demand for each customer and time period, and then use these estimates as inputs for your vehicle routing model. This way, you can design routes and schedules that can accommodate the fluctuations and changes in demand, and avoid unnecessary trips or delays.