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Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419
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Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Dec 23, 2015

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Page 1: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Stochastic Inventory Theory

Professor Stephen R. LawrenceLeeds School of BusinessUniversity of ColoradoBoulder, CO 80309-0419

Page 2: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Stochastic Inventory Theory

Single Period Stochastic Inventory Model “Newsvendor” model

Multi-Period Stochastic Inventory Models Safety Stock Calculations Expected Demand & Std Dev Calculations Continuous Review (CR) models Periodic Review (PR) models

Page 3: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Single Period Stochastic Inventory

“Newsvendor” Model

Page 4: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Single-Period Independent Demand “Newsvendor Model:” One-time buys of

seasonal goods, style goods, or perishable items

Examples: Newspapers, Christmas trees; Supermarket produce; Fad toys, novelties; Fashion garments; Blood bank stocks.

Page 5: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Newsvendor Assumptions

Relatively short selling season; Well defined beginning and end; Commit to purchase before season starts; Distribution of demand known or estimated; Significant lost sales costs (e.g. profit); Significant excess inventory costs.

Page 6: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Single-Period Inventory Example

A T-shirt silk-screening firm is planning to produce a number of custom T-shirts for the next Bolder Boulder running event. The cost of producing a T-shirt is $6.00, with a selling price of $12.00. After BB concludes, demand for T-shirts falls off, and the manufacturer can only sell remaining shirts for $3.00 each. Based on historical data, the expected demand distribution for BB T-shirts is:

How many T-shirts should the firm produce to maximize profits?

Quantity Probability Cumulative

1000 0.00 0.00

2000 0.05 0.05

3000 0.15 0.20

4000 0.40 0.60

5000 0.30 0.90

6000 0.10 1.00

Page 7: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Opportunity Cost of Unmet Demand

Define:

U = opportunity cost of unmet demand (underproduce - understock)

Example:

U = sales price - cost of production

= 12 - 6

= $6 lost profit / unit

Page 8: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Cost of Excess Inventory

Define:

O = cost of excess inventory

(overproduce - overstock)

Example:

O = cost of production - salvage price

= 6 - 3

= $3 loss/unit

Page 9: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Solving Single-Period Problems

Where Pr(x≤Q*) is the “critical fractile” of the demand distribution.

ExampleU = cost of unmet demand (understock) U = 12 - 6 = 6 profitO = cost of excess inventory (overstock) O = 6 - 3 = 3 loss

Produce/purchase quantity Q* that satisfies the ratio

Optimal Solution:

OU

UQx

)Pr( *

Page 10: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Translation to Textbook Notation

Lawrence Textbook

Understock cost U Cus

Overstock cost O Cos

Probability of understocking

Pr(xQ) Pus

Critical fractile Pr(xQ)Critical fillrate (cfr)

Page 11: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Alternate Solution

Where Pr(x>Q*) is the “critical fractile” that represents the probability of a stockout when starting with an inventory of Q* units.

Produce/purchase quantity Q* that satisfies the ratio

OU

O

OU

UQxQx

1)Pr(1)Pr( **

Some textbooks use an alternative representation of the critical fractile:

NOTE: to use a standard normal Z-table, you will need Pr(x≤Q*), NOT Pr(x>Q*)

Page 12: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Solving Single-Period Problems

ExampleU = cost of unmet demand (underage) U = 12 - 6 = 6 profitO = cost of excess inventory (overage) O = 6 - 3 = 3 loss

Example:

Pr(x ≤ Q) = 6 / ( 3 + 6 ) = 0.667

Page 13: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Solving Single-Period Problems

D

0.00

0.20

0.40

0.60

0.80

1.00

1000 2000 3000 4000 5000 6000

Quantity (Q)

Pro

bab

ility

P(x

<Q)

0.667

4,222

Page 14: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Inventory Spreadsheet

Page 15: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Multi-Period Stochastic Inventory Models Continuous Review (CR) models

Periodic Review (PR) models

Page 16: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Key Assumptions

Demand is probabilistic Average demand changes slowly Forecast errors are normally distributed with

no bias Lead times are deterministic

Page 17: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Key Questions

How often should inventory status be determined?

When should a replenishment order be placed?

How large should the replenishment be?

Page 18: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Types of Multi-Period Models

(CR) continuous review Reorder when inventory falls to R (fixed) Order quantity Q (fixed) Interval between orders is variable

(PR) periodic review Order periodically every T periods (fixed) Order quantity q (variable) Inventory position I at time of reorder is variable

Many others…

Page 19: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Notation B = stockout cost per item TAC = total annual cost of inv. L = order leadtime D = annual demand d(L) = demand during leadtime h = holding cost percentage H = holding cost per item I = current inventory position

Q = order quantity (fixed) Q* = optimal order quantity q = order quantity (variable) T = time between orders R = reorder point (ROP) S = setup or order cost SS = safety stock C = per item cost or value.

Page 20: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Demand Calculations

Page 21: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Demand over Leadtime

Multiply known demand rate D by leadtime L Be sure that both are in the same units!

Example Mean demand is D = 20 per day Leadtime is L= 40 days d(L) = D x L = 20 x 40 = 800 units

Page 22: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Demand Std Deviation over Leadtime Multiply demand variance 2 by leadtime L Example

Standard deviation of demand = 4 units per day Calculate variance of demand 2 = 16 Variance of demand over leadtime L=40 days is

L2 = L 2 = 40×16=640

Standard deviation of demand over leadtime L is L = [L 2]½ = 640½ = 25.3 units

Remember Variances add, standard deviations don’t!

Page 23: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Safety Stock Calculations

Page 24: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Safety Stock Analysis

The world is uncertain, not deterministic demand rates and levels have a random component delivery times from vendors/production can vary quality problems can affect delivery quantities Murphy lives

safety stock

RL

time

Inventory Level

Q

0stockout!

SS

Page 25: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Inventory / Stockout Trade-offs

InventoryLevel

R

SS

0time

R

SS

SS

R

Large safety stocks Few stockouts

High inventory costs

Small safety stocks Frequent stockoutsLow inventory costs

Balanced safety stock, stockout frequency,

inventory costs

Page 26: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Safety Stock Example Service policies are often set by management

judgment (e.g., 95% or 99% service level) Monthly demand is 100 units with a standard deviation

of 25 units. If inventory is replenished every month, how much safety stock is need to provide a 95% service level? Assume that demand is normally distributed.

4225.412565.195.0 LzSS

Alternatively, optimal service level can be calculated using “Newsvendor” analysis

Page 27: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Continuous Review (CR) Stochastic Inventory Models

Page 28: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Always order the same quantity Q Replenish inventory whenever inventory level falls below

reorder quantity R Time between orders varies Replenish level R depends on order lead-time L Requires continuous review of inventory levels

RQ Q

Q

Q

L

time

Inventory Level

(CR) Continuous Review System

Page 29: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Safety Stock and Reorder Levels

Reorder Level = Safety Stock + Mean Demand over Leadtime

R = SS + DL

L

Distribution of demand over leadtime L

Stockout!

InventoryLevel

time

R

SS

0

DL

Page 30: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(CR) Order-Point, Order-Quantity

Continuous review system Useful for class A, B, and C inventories Replenish when inventory falls to R; Reorder quantity Q. Easy to understand, implement “Two-bin” variation

Page 31: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(CR) Implementation

Implementation Determine Q using EOQ-type model Determine R using appropriate safety-stock model

Practice Reserve quantity R in second “bin” (i.e. a baggy) Put order card with second bin Submit card to purchasing when second bin is

opened Restock second bin to R upon order arrival

Page 32: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(CR) Example

Consider a the following product D = 2,400 units per year C = $100 cost per unit h = 0.24 holding fraction per year (H = hC = $24/yr) L = 1 month leadtime S = $ 200 cost per setup B = $ 500 cost for each backorder/stockout L = 125 units per month variation

Management desires to maintain a 95% in-stock service level.

Page 33: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(CR) Example

20012/400,2 LD

200)100)(24.0(

2400)(200(22* hC

SDQ

406206200)125(65.1200

200 95.0

R

zSSDR LL

Whenever inventory falls below 406, place another order for 200 units

Page 34: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Total Inventory Costs for CR Policies TAC = Total Annual Costs TAC = Ordering + Holding + Expected Stockout Costs

1004430073442400

)05.0(200

2400500

2

20020624

200

2400200

)Pr(2

TAC

TAC

QdQ

DB

QSSH

Q

DSTAC

TAC = $10,044 per year (CR policy)

Page 35: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Periodic Review (PR) Stochastic Inventory Models

Page 36: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Multi-Period Fixed-Interval Systems

Requires periodic review of inventory levels Replenish inventories every T time units Order quantity q (q varies with each order)

T TT

L L L

I

II

Inve

nto

ry L

evel

time

q

q

q

Page 37: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Periodic Review Details Order quantity q must be large enough to cover

expected demand over lead time L plus reorder period T (less current inventory position I )

Exposed to demand variation over T+L periods

T TT

L L L

I

II

Inve

nto

ry L

evel

time

q

q

q

Page 38: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(PR) Periodic-Review System

Periodic review (often Class B,C inventories) Review inventory level every T time units Determine current inventory level I Order variable quantity q every T periods Allows coordinated replenishment of items Higher inventory levels than continuous

review policies

Page 39: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(PR) Implementation

Implementation Determine Q using EOQ-type model; Set T=Q/D (if possible --T often not in our control) Calculate q as sum of required safety stock,

demand over leadtime and reorder interval, less current inventory level

Practice Interval T is often set by outside constraints E.g., truck delivery schedules, inventory cycles, …

Page 40: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(PR) Policy Example Consider a product with the following

parameters: D = 2,400 units per year C = $100 h = 0.24 per year (H = hC = $24/yr) T = 2 months between replenishments L = 1 month S = $200 B = $500 cost for each backorders/stockouts I = 100 units currently in inventory L= 125 units per month variation

Management desires to maintain a 95% in-stock service level.

Page 41: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

(PR) Policy ExamplemonthsT 2

900857100357600

100)51.216(65.1600

)()( 95.0

q

q

IzLTdISSLTdq LT

mosmomosLT 312

600200400)()()( LdTdLTd

unitsLT 51.216)125(3 2

Suppose that this is given by circumstances…

Page 42: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Total Inventory Costs for PR Policies TAC = Total Annual Costs TAC = Ordering + Holding + Expected Stockout Costs

14718150133681200

)05.0)(6(5002

40035724)6(200

)Pr(2

TAC

TAC

QdQ

DB

QSSH

Q

DSTAC

TAC = $14,718 per year (PR policy)

Page 43: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Further Information

American Production and Inventory Control Society (APICS) www.APICS.org

Professional organization of production, inventory, and resource managers

Offers professional certifications in production, inventory, and resource management

Page 44: Stochastic Inventory Theory Professor Stephen R. Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419.

Further Information

Institute for Supply Management (www.ISM.ws) Previously the National Association of Purchasing

Managers (NAPM) Professional organization of supply chain

managers Offers certifications in supply chain

management