ShipSmart TM : The Model and the Computer Science

1. ShipSmartTM:The Model and the Computer Science Jonathan Sheffi University of Maryland College Park April 17, 2000

2. Outline • The EOQ Model • Reliability and Safety Stock • Internal Structure of ShipSmart • ShipSmart™ Example • Object-Oriented Programming

3. Tradeoff: Production Batch vs. Inventory similar to Tradeoff: Shipment Size vs. Inventory • Production setup costs vs. Inventory carrying costs • Transportation costs vs. Inventory carrying costs Lot Size Inventory

4. In Stock Time Economic Order Quantity Model A simple business: • Order fixed quantity of goods at fixed intervals • Sell at constant rate Inventory costs = quantity x time

5. A Single Receiving Cycle

6. A Single Receiving Cycle

7. A Single Receiving Cycle X

8. A Single Receiving Cycle X

9. A Single Receiving Cycle X Y Smaller (and more frequent) shipments imply lower inventory carrying costs

10. Smaller shipments • low inventory costs • high transportation costs Large shipments • high inventory costs • low transportation costs Inventory cost-in transit Tradeoffs: In addition:

11. Inventory Costs Inventory Carrying Costs/Unit In-Transit Inventory Shipment Size

12. Transportation Costs LTL Rate Formula rate curve Actual rate curve Shipment Size

13. Basic Tradeoffs COSTS ($/item) Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

14. Basic Tradeoffs COSTS ($/item) Transportation costs Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

15. Basic Tradeoffs COSTS ($/item) Cycle inventory costs Transportation costs Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

16. Basic Tradeoffs COSTS ($/item) Cycle inventory costs Transportation costs In-Transit Inventory Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

17. Basic Tradeoffs COSTS ($/item) Cycle inventory costs Total inventory costs Transportation costs In-Transit Inventory Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

18. Basic Tradeoffs COSTS ($/item) Total logistics costs Cycle inventory costs Total inventory costs Transportation costs In-Transit Inventory Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

19. Basic Tradeoffs COSTS ($/item) Total logistics costs Cycle inventory costs Total inventory costs Transportation costs In-Transit Inventory Opt. size Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

20. Basic Tradeoffs COSTS ($/item) Total logistics costs Cycle inventory costs Least cost Total inventory costs Transportation costs In-Transit Inventory Opt. size Shipment Size (items/shipment) Logistics Cost Components as a Function of Shipment Size

21. Elements of Total Logistics Costs Transportation Costs Cycle Inventory Costs In Transit Inventory Costs Safety Stock Costs Other Costs TotalLogistics Cost

22. Optimal Shipment Size 2 * (Transportation costs) (Demand rate) = (Cycle Inventory Costs) Total Logistics Costs 2 * (Cycle Inventory Costs) (Transportation Costs) = (Demand Rate) In-transit Inventory Costs Safety Stock Costs Other Costs Analytical Expressions

23. Transit Times Transit delivery times vary in random fashion. Each mode and carrier is characterized by a distribution of delivery times.

24. Inventory Time Effect of Shipment Delay Regular on-time delivery

25. Effect of Shipment Delay Inventory Time Delay One delivery delayed

26. Effect of Shipment Delay Inventory Time Delay Delivery pattern with a single delay

27. Effect of Shipment Delay Inventory Time Delay Erratic delivery pattern

28. Effect of Safety Stock Inventory Time Safety stock level

29. Effect of Safety Stock Inventory Time Avoiding stock-out

30. Transit Time Density Function Probability Transit Time

31. Transit Time Density Function Probability Transit Time Average Time

32. Transit Time Density Function Probability Transit Time Average Time 95 Percentile

33. Transit Time Density Function Probability Safety Time Transit Time Average Time 95 Percentile

34. Transit Time Density Function Probability Safety Time Transit Time Average Time 95 Percentile Safety Stock for 95% Fill Rate = (Safety Time) x (Sales Rate)

36. The Internal Structure • Calculations are performed for each option separately • In case there is one segment: • Optimal shipment size is calculated using the EOQ formula • Takes into account minimum frequency and storage capacity • Calculates all other output values

37. The Internal Structure • For multiple segments: • Rank vehicle capacities • Find how many vehicles are needed for each segment • Loop over the second largest, third largest, etc. • Use optimal solution to calculate all output values (including the segment solutions)

38. ShipSmart Example

39. Tactics for the Rail Operator • Reduce shipment price • Tighten delivery time • Tighten reliability • Compete for lower valued commodities • Compete for commodities which ship in high volume

40. Procedural vs. OOP • Procedural programming: • Organize system around procedures that operate on data (do-something <data> <arg> ...) (do-another-thing <data>) • Object-oriented programming: • Organize system around objects that receive messages (<object> 'do-something <arg>) (<object> 'do-another-thing) • An object encapsulates data and operations

41. Advantages of OOP • Simplicity: software objects model real world objects, so the complexity is reduced and the program structure is very clear • Modularity: each object forms a separate entity whose internal workings are decoupled from other parts of the system • Modifiability: it is easy to make minor changes in the data representation or the procedures in an OO program. Changes in the behavior of an object do not affect any other part of a program, since the only public interface that the external world has to an object is through messages • Extensibility: adding new features or responding to changing operating environments can be solved by introducing a few new objects and modifying some existing ones • Maintainability: objects can be maintained separately, making locating and fixing problems easier • Reusability: objects can be reused in different programs

42. Elements of OOP • Class: • specifies the common behavior of entities • Instance: • A particular object or entity of a given class

43. PLANET TORPEDO SHIP position: velocity:target:proximity-fuse: position: position: velocity:num-torps: POSITION PLANET? DISPLAYCLOCK-TICK TORPEDO? POSITION VELOCITY MOVEDISPLAYCLOCK-TICK POSITION VELOCITY MOVE SHIP?ATTACK DISPLAY CLOCK-TICKEXPLODE Space War Class Diagram

44. PLANET TORPEDO SHIP position: velocity:target:proximity-fuse: position: position: velocity:num-torps: POSITION PLANET? DISPLAYCLOCK-TICK TORPEDO? POSITION VELOCITY MOVEDISPLAYCLOCK-TICK POSITION VELOCITY MOVE SHIP?ATTACK DISPLAY CLOCK-TICKEXPLODE Space War Class Diagram • Ships and torpedoes have some behavior that is the same – is there are way to capture this commonality?

45. MOBILE-THING PLANET TORPEDO SHIP position: velocity: target:proximity-fuse: position: num-torps: MOBILE-THING? POSITION VELOCITY MOVE POSITION PLANET? DISPLAYCLOCK-TICK is-a is-a TORPEDO? DISPLAYCLOCK-TICK SHIP?ATTACK DISPLAY CLOCK-TICKEXPLODE has-atarget Space war game with Inheritance • SHIP class is a specialization or sub-class of the MOBILE-THING class • SHIPis-aMOBILE-THING • SHIPinherits the state and behavior of MOBILE-THING • MOBILE-THING class is a super-classof the SHIP and TORPEDO classes

46. ? Any Questions? ? ? ? ? ? Jon Sheffi jsheffi@mit.edu