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ESD Faculty Lunch Research Talk Mustafa Çağrı Gürbüz

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

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ESD Faculty Lunch Research Talk Mustafa Çağrı Gürbüz

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  1. ESD Faculty Lunch Research Talk Mustafa Çağrı Gürbüz April 14, 2009 CTL @ MIT

  2. 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

  3. 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

  4. Coordinated Replenishment Across Retailers & Suppliers Mustafa Cağrı Gürbüz MIT-Zaragoza International Logistics Program, Zaragoza, Spain Co-authors: Kamran Moinzadeh, Yong-Pin Zhou University of Washington, Michael G. Foster School of Business

  5. 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

  6. 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

  7. Savings from fixed inbound ordering costs Supplier 1 Supplier 2 Inbound Shipment 1: Costs “$K01” Takes “L01” time units Inbound Shipment 2: Costs “$K02” Takes “L02” time units Distribution Center Savings from fixed outbound ordering costs Retailer 1 Retailer 2 Retailer N Outbound Shipments: Each costs “$K” and takes “L” time units Coordinated replenishment (two-items) Order trigger at all retailers, combined

  8. 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?

  9. Analysis Cost Rate Inventory level distribution Inbound quantity distribution Inbound penalty cost Holding/Shortage cost Ordering cost Outbound penalty cost Inventory position distribution Expected cycle time Outbound quantity distribution

  10. 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 jwhenever • any retailer’s inventory position for item jdrops to sj OR • thetotal demand at all the retailers for item j reaches Qj (for j=1,…M).

  11. Coordination across retailers & items (suppliers) Policy MISO-1: • Consider Sub-policyj 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 iwhen 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-policyj • Pick the sub-policy with the minimum cost rate.

  12. Illustration of Policy MISO-1 Item 2 is shipped out from Supplier 2 0 0 t t t+o2 t+l12 t+L01 1) Trigger for Item 1 (or Item 2) 2) Raise the inventory position for Item 1 and Item 2 3) Item 1 is shipped out from Supplier 1 1) Both items arrive at the warehouse at the same time 2) They are shipped to the retailers

  13. Coordination across retailers & items (suppliers) Policy MISO-2: • Consider Sub-policyj 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 iand 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-policyj • Pick the sub-policy with the minimum cost rate.

  14. Illustration of Policy MISO-2 1) Raise the inventory position for Item 2 2) Item 2 is shipped out from Supplier 2 0 0 t t t+o2 t+l12 t+L01 1) Trigger for Item 1 (or Item 2) 2) Raise the inventory position for Item 1 3) Item 1 is shipped out from Supplier 1 1) Both items arrive at the warehouse at the same time 2) They are shipped to the retailers

  15. 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).

  16. Illustration of Policy MISO-3: 1) Item 2 is shipped out from Supplier 2 0 0 t t t+o2 t+l12 t+L01 1) Trigger for Item 1 OR 2 2) Raise the inventory position for items 1 and 2 3) Item 1 is shipped out Supplier 1 1) Both items arrive at the warehouse at the same time 2) They are shipped to the retailers

  17. 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 jexactly 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.

  18. Illustration of Policy MISO-4: 1) Raise the inventory position for Item 2 2) Item 2 is shipped out from Supplier 2 0 0 t t t+o2 t+l12 t+L01 1) Trigger for Item 1 OR 2 2) Raise the inventory position for Item 1 3) Item 1 is shipped out Supplier 1 1) Both items arrive at the warehouse at the same time 2) They are shipped to the retailers

  19. Summary of Coordinated (across items) continuous review policies MISO-2: 1. Monitor IP for one item only 2. Internal delay MISO-1: 1. Monitor IP for one item only 2. External delay MISO-3: 1. Monitor IP for all items 2. External delay MISO-4: 1. Monitor IP for all items 2. Internal delay

  20. 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 .

  21. 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)

  22. Revenue Management? • What is it? • Pricing train seats for specific market segments • Protecting seats for each segment based on demand (capacity allocation) • Why should passenger rail companies use it? • Unfilled train seats = Lost Revenue • Full trains = Lost Revenue • Why should YOU care? • Understanding it can help you save money Borrowed from S. Joiner

  23. A Simple Example Revenue Management Discounting No Revenue Management • Pricing Scheme: Departure Day Departure Day Departure Day -14 Days -14 Days -14 Days -7 Days -7 Days -7 Days 50€ 30€ 50€ 30€ 30€ 50€ 30€ 20€ 50€ (Max 4) (Max 14) Seat Utilization: 100% Total Revenue: 2470€ Revenue per Seat: 45,33€ Seat Utilization: 65% Total Revenue: 1850€ Revenue per Seat: 32,50€ Total Revenue Summary No RM: 1850€ Seat Utilization: 93% Total Revenue: 1590€ Revenue per Seat: 28,90€ Discount: 1590€

  24. Why is this so difficult? Barcelona Madrid Zaragoza • Data Limitations: • Limited historical data is available • Historical data does not help understand how customers will respond to price changes • The Rail Network: • Unlike in the previous example, passengers can enter and exit the train at various locations during a trip • A seat protected for the Zaragoza-Barcelona leg means one less seat is available for the Madrid-Barcelona leg Borrowed from S. Joiner

  25. The Research • Question: • What general guidelines can be established for applying revenue management in the passenger rail industry? • Approach: • Using historical passenger data and customer surveys from RENFE to understand and predict consumer behavior • Simulation: • Developed a simulation model to see how different seat protection and pricing schemes affect revenue Borrowed from S. Joiner

  26. 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

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