ESD Faculty Lunch Research Talk

Mustafa Çağrı Gürbüz

April 14, 2009

CTL @ MIT

Introduction• BS in Industrial Engineering, Bilkent University, Ankara

Turkey, 1999

• MS in Industrial Engineering, Bilkent University, Ankara Turkey, 2001

• PhD in Operations Management, Michael G. Foster School of Business, University of Washington, 2006

• Faculty member at the Zaragoza Logistics Center since 09/2006– Visiting faculty at CTL until 09/2009

Agenda• Academic Research

– Inventory/Transportation Management in Distribution Systems

• “Coordinated Replenishment Strategies in Inventory/Distribution Systems”, with K. Moinzadeh and Y. Zhou, Management Science, Vol. 53 (2), 2007, 293-307.

– Inventory Management under random supply• “Supplier Diversification Under Binomial Yield”, with M. Fadıloğlu and E.

Berk, Operations Research Letters, Vol. 36 (5), 2008, 539-542. – Contracting retailer/manufacturer efforts in a newsboy setting – Impact of random deal offerings for perishable products under

continuous review– The impact of accountability on the bullwhip factor

• • Projects at ZLC

– Revenue Management for the passenger rail industry – Measuring carbon footprint due to transportation for the European

distribution of Print Green– Investigating Spain’s potential in distributing goods in Europe

Coordinated Replenishment Across Retailers & Suppliers

Mustafa Cağrı GürbüzMIT-Zaragoza International Logistics Program, Zaragoza, Spain

Co-authors: Kamran Moinzadeh, Yong-Pin ZhouUniversity of Washington, Michael G. Foster School of Business

Distribution Costs!• Distribution costs are cited as 10% of GDP for developed

countries, and 20% or more for developing countries (a World Bank research paper by Bagai and Wilson, 2006)

• Distribution costs represent on average 15% of the selling price (Van Damme 2000) in European companies– 32%: transportation costs– 31%: inventory costs– 28%: facility costs

• Industry Week Value Chain Survey conducted in 2005 (www.industryweek.com) – The percentage of respondents stating more than 10%

increase in distribution costs of sales has more than doubled since 2003

Borrowed from Dr. Emre Berk

Consolidation/Coordination• Majority of the companies use some form of

shipment consolidation meaning:– Combining multiple shipments into a single

group (across time, locations, products) to achieve lower costs• Time based consolidation• Quantity based consolidation• Time and quantity based

Coordinated replenishment (two-items)

Outbound Shipments: Each costs “$K” and takes “L” time units

DistributionCenter

Supplier 1

Retailer 1 Retailer 2 Retailer N

Supplier 2

Inbound Shipment 2: Costs “$K02” Takes “L02” time units

Inbound Shipment 1: Costs “$K01” Takes “L01” time units

Savings from fixed outboundordering costs

Savings from fixed inboundordering costs

Order trigger at all retailers, combined

Challenges– Use of information to decide;

• How to coordinate shipments? – When to order?– How much to order?

– GOAL: To minimize the overall cost, which is the sum of:

• Fixed Ordering/Setup, • Holding/Backorder, • Transportation.

– The optimal solution to this problem?

Analysis

Inbound quantitydistribution

Expected cycle time

Outbound quantitydistribution

Inventory positiondistribution

Inventory leveldistribution

Inbound penaltycost

Outbound penaltycost

Orderingcost

Holding/Shortagecost

Cost Rate

Coordination across retailers alone

• Each item is ordered independently– but retailers are replenished simultaneously

• Policy MII0: The warehouse orders to raise all the retailers’ inventory position to Sj for item j whenever– any retailer’s inventory position for item j drops to sj

OR– the total demand at all the retailers for item j reaches

Qj (for j=1,…M).

Coordination across retailers & items (suppliers)

Policy MISO-1:

• Consider Sub-policy j for all j=1,2,..,M :– Monitor IP for item j only,

• Trigger Mechanism: Replenishment happens whenever:

– any retailer’s inventory position for item j drops to sj or

– the total demand at all the retailers for item j reaches Qj.

• Dispatch Mechanism:

– Raise all the retailers’ inventory position to Si for item i when the replenishment is triggered,

– Ask the supplier to ship item i exactly l1i (L01-L0i) time units after replenishment is triggered (assume L01≥L0i for all i).

• Evaluate the cost rate for Sub-policy j• Pick the sub-policy with the minimum cost rate.

Illustration of Policy MISO-1

0 t t+o2 t+L01

1) Trigger for Item 1 (or Item 2)2) Raise the inventory positionfor Item 1 and Item 23) Item 1 is shipped out fromSupplier 1

Item 2 is shipped out from Supplier 2

1) Both items arrive at thewarehouse at the same time2) They are shipped to theretailers

0 t t+l12

Coordination across retailers & items (suppliers)

Policy MISO-2:

• Consider Sub-policy j for all j=1,2,..,M :– Monitor IP for item j only,

• Trigger Mechanism: Replenishment happens whenever:

– any retailer’s inventory position for item j drops to sj or

– the total demand at all the retailers for item j reaches Qj.

• Dispatch Mechanism:

– Raise all the retailers’ inventory position to Si for item i and ask the supplier to ship item i exactly l1i (L01-L0i) time units for all i after replenishment is triggered (assume L01≥L0i for all i).

• Evaluate the cost rate for Sub-policy j• Pick the sub-policy with the minimum cost rate.

Illustration of Policy MISO-2

0 t t+o2 t+L01

1) Trigger for Item 1 (or Item 2) 2) Raise the inventory positionfor Item 1 3) Item 1 is shipped out fromSupplier 1

1) Raise the inventory positionfor Item 2 2) Item 2 is shipped out from Supplier 2

1) Both items arrive at thewarehouse at the same time2) They are shipped to theretailers

0 t t+l12

Coordination across retailers & items (suppliers)

Policy MISO-3:• Monitor IP for all items,

– Trigger Mechanism: Replenishment happens whenever:

• any retailer’s inventory position for any item j drops to sj or

• the total demand at all the retailers for any item j reaches Qj.

– Dispatch Mechanism:

• Raise all the retailers’ inventory position to Sj for item j (all items j=1,2,..,M) when the replenishment is triggered,

• Ask the supplier to ship item j exactly l1j (L01-L0j) time units after replenishment has been triggered (assume L01≥L0j for all j).

Illustration of Policy MISO-3:

0 t t+o2 t+L01

1) Trigger for Item 1 OR 22) Raise the inventory positionfor items 1 and 23) Item 1 is shipped out Supplier 1

1) Item 2 is shipped out from Supplier 2

1) Both items arrive at thewarehouse at the same time2) They are shipped to theretailers

0 t t+l12

Coordination across retailers & items Policy MISO-4:• Monitor IP for all items,

– Trigger Mechanism: Replenishment happens whenever:• any retailer’s inventory position for any item j drops to sj or • the total demand at all the retailers for any item j reaches Qj.

– Dispatch Mechanism: • Raise all the retailers’ inventory position to Sj for item j exactly l1j

(L01-L0j) time units after replenishment has been triggered,• Ask the supplier to ship item j exactly l1j (L01-L0j) time units after

replenishment has been triggered (assume L01≥L0j for all j).

• Assume no trigger will happen for item j for the next ljM time units after the inventory position is raised to Sj for j=1,..,M-1.

Illustration of Policy MISO-4:

0 t t+o2 t+L01

1) Trigger for Item 1 OR 22) Raise the inventory positionfor Item 13) Item 1 is shipped out Supplier 1

1) Raise the inventory position for Item 22) Item 2 is shipped out from Supplier 2

1) Both items arrive at thewarehouse at the same time2) They are shipped to theretailers

0 t t+l12

Summary of Coordinated (across items) continuous review policies

MISO-1:

1. Monitor IP for one item only

2. External delay

MISO-2:

1. Monitor IP for one item only

2. Internal delay

MISO-3:

1. Monitor IP for all items

2. External delay

MISO-4:

1. Monitor IP for all items

2. Internal delay

Numerical Results

• No significant difference between coordination through internal or external delay:– Policies MISO_3 and MISO_4 perform very closely

• Policies MISO_1 and MISO_2 are good heuristics: – Their performance are pretty close to that of Policies MISO_3

and MISO_4 in many cases– Easier to analyze and compute

• Rankings (best-worst) of the policies are as follows (the % improvement over the MIIO is given in parentheses): – MISO_3 (2.12%), MISO_4 (1.82%), MISO_2 (0.59%), and MISO_1

(0.42%)

• Monitoring inventory positions for both items help Policies MISO_3 and MISO_4 for higher .

Numerical Results

• Benefits from coordination across items increase for:– More retailers (higher N)

– Larger fixed inbound/outbound ordering costs (higher K0 and K/

K0) – Larger outbound truck capacities (higher C)– Smaller unit outbound transportation penalty cost inbound

(smaller )– Smaller difference in transit times from supplier to warehouse

(larger L02/ L01)

Revenue Management?• What is it?

o Pricing train seats for specific market segmentso Protecting seats for each segment based on demand

(capacity allocation)

• Why should passenger rail companies use it?o Unfilled train seats = Lost Revenueo Full trains = Lost Revenue

• Why should YOU care? Understanding it can help you save money

Borrowed from S. Joiner

A Simple Example

Seat Utilization: 93%

Total Revenue: 1590€

Revenue per Seat: 28,90€

Departure Day-14 Days -7 Days

50€ 50€ 50€

Departure Day-14 Days -7 Days

30€ 30€ 30€

Departure Day-14 Days -7 Days

20€ 30€ 50€

No Revenue Management• Pricing Scheme:

Seat Utilization: 100% Total Revenue: 2470€ Revenue per Seat: 45,33€

Seat Utilization: 65% Total Revenue: 1850€ Revenue per Seat: 32,50€

DiscountingRevenue Management

Total Revenue Summary

No RM: 1850€Discount: 1590€

(Max 4) (Max 14)

Why is this so difficult?• Data Limitations:

o Limited historical data is availableo Historical data does not help understand how customers

will respond to price changes

• The Rail Network:o Unlike in the previous example, passengers can enter

and exit the train at various locations during a tripo A seat protected for the Zaragoza-Barcelona leg means

one less seat is available for the Madrid-Barcelona leg

BarcelonaZaragozaMadridBorrowed from S. Joiner

The Research• Question:

o What general guidelines can be established for applying revenue management in the passenger rail industry?

• Approach:o Using historical passenger data and customer surveys

from RENFE to understand and predict consumer behavior

• Simulation:o Developed a simulation model to see how different seat

protection and pricing schemes affect revenue

Borrowed from S. Joiner

Contact information

• Email: – mgurbuz@zlc.edu.es– mgurbuz@mit.edu

• Address: – Avda. Gomez Laguna, 25, Planta 1,50009 Zaragoza, Spain

• Phone: – +34 619 44 62 66