Glossary · approach
MIP
An optimization model where some decision variables are forced to be whole numbers (e.g. number of trucks, number of shifts).
Mixed Integer ProgrammingMixed Integer Linear ProgrammingMILP
MIP (Mixed Integer Programming) handles 'whole number' decisions: 'How many trucks do I use? 3 or 4? — half a truck doesn't exist.' Different from pure-math optimization: some variables can't be fractional. Job shop scheduling, vehicle routing (VRP), and lot sizing are all MIP problems.
Örnek
Shift planning: '5 shifts' or '6 shifts' — you can't run 5.3 shifts. MIP handles this naturally.
Where this term appears
- Problems A New Part Order Arrives — How Do I Get the Optimal Operation Sequence + Machine Choice + Setup?
- Problems Backward from the Customer Order — Which Raw Material, When, and How Much Should I Order?
- Problems Dozens of SKUs from the Same Supplier — At What Frequency Do I Order Each So Trucks and Stock Cost Are Minimum Together?
- Problems Fixed Budget, Many Candidate Projects — Which Subset Should I Pick So That Total Return Is Maximised?
- Problems From One Node to Another — How Do I Compute the Shortest Path on a Weighted Graph?
- Problems How Do I Balance Production Rate, Inventory, Overtime and Subcontracting Over the Next 12 Months?
- Problems How Do I Build Weekly Employee Patterns — Demand Met, Rest, Hours and Fairness All Holding Together?
- Problems How Do I Cut This Order with the Least Waste?
- Problems How Do I Draw the Fixture — Which Match in Which Week?
- Problems How Do I Lay Out Outpatient Appointments — Keeping Patient Wait and Doctor Idle Time Both Low?
- Problems How Many Items Do I Sample From an Incoming Lot, and How Many Defects Do I Allow — Inspection Cost vs Customer Complaint Trade-off?
- Problems How Much Cash in Which ATM, How Often to Refill — Balancing Empty-ATM Complaints Against High Immobilisation Cost