Mapping Allows You to Visualize Your Supply Chain
Mapping Allows You to Visualize Your Supply Chain
Displaying the Solutions Allows You to Compare Scenarios Think-Pair-Share Take 2 min.to consider: For the two designs, Which one is more effective? What objective does each design have?
Displaying the Solutions Allows You to Compare Scenarios Think – Pair – Share Take 2 min. to consider: For the two designs, Which one is more effective? What objective does each design have?
Data for Network Design 1.A listing of all products 2.Location of customers,stocking points and sources 3.Demand for each product by customer location 4.Transportation rates 5.Warehousing costs 6.Shipment sizes by product 7.Order patterns by frequency,size,season,content 8.Order processing costs 9.Customer service goals
Data for Network Design 1. A listing of all products 2. Location of customers, stocking points and sources 3. Demand for each product by customer location 4. Transportation rates 5. Warehousing costs 6. Shipment sizes by product 7. Order patterns by frequency, size, season, content 8. Order processing costs 9. Customer service goals
Too Much Information The amount of data involved in any optimization model is overwhelming The first step is data aggregation. Customers are aggregated using a grid network or other clustering techniques. Items are aggregated into a reasonable number of product groups. data aggregation:数据汇集
Too Much Information The amount of data involved in any optimization model is overwhelming. The first step is data aggregation. Customers are aggregated using a grid network or other clustering techniques. Items are aggregated into a reasonable number of product groups. data aggregation：数据汇集
Why Aggregate? The reasons for data aggregation: The cost of obtaining and processing data The form in which data is available The size of the resulting location model The accuracy of forecast demand 1.Our ability to forecast customer demand is poor. 2.The variability in forecast demand can be reduced through aggregating data. 3.It is the basis of risk pooling concept
Why Aggregate? The reasons for data aggregation: The cost of obtaining and processing data The form in which data is available The size of the resulting location model The accuracy of forecast demand 1. Our ability to forecast customer demand is poor. 2. The variability in forecast demand can be reduced through aggregating data. 3. It is the basis of risk pooling concept