Tata Institute of Fundamental Research
Asymptotic Optimality of Constant-Order Policies for Lost Sales Inventory Models with Large Lead Times
Seminar
Speaker:
Professor David A. Goldberg (Georgia Institute of Technology
H. Milton Stewart School of Industrial
and Systems Engineering
765 Ferst Drive
Room 437 Groseclose
United States of America)
Organiser:
Sandeep K Juneja
Date:
Thursday, 2 Jan 2014, 11:30 to 12:30
Venue:
AG-80
(Scan to add to calendar)
Abstract:
Abstract: Lost sales inventory models with large lead times, which arise in many practical settings, are notoriously difficult to optimize due to the curse of dimensionality. In this talk we show that when lead times are large, a very simple constant-order policy, first studied by Reiman, performs nearly optimally. The main insight of our work is that when the lead time is very large, such a significant amount of randomness is injected into the system between when an order for more inventory is placed and when that order is received, that ``being smart" algorithmically provides almost no benefit. Our main proof technique combines a novel coupling for suprema of random walks with arguments from queueing theory (this is joint work with Dmitriy A. Katz-Rogozhnikov, Yingdong Lu, Mayank Sharma, and Mark S. Squillante from IBM T.J. Watson Research Center).
| Speaker: | Professor David A. Goldberg (Georgia Institute of Technology H. Milton Stewart School of Industrial and Systems Engineering 765 Ferst Drive Room 437 Groseclose United States of America) |
| Organiser: | Sandeep K Juneja |
| Date: | Thursday, 2 Jan 2014, 11:30 to 12:30 |
| Venue: | AG-80 |
(Scan to add to calendar)
Abstract:
Abstract: Lost sales inventory models with large lead times, which arise in many practical settings, are notoriously difficult to optimize due to the curse of dimensionality. In this talk we show that when lead times are large, a very simple constant-order policy, first studied by Reiman, performs nearly optimally. The main insight of our work is that when the lead time is very large, such a significant amount of randomness is injected into the system between when an order for more inventory is placed and when that order is received, that ``being smart" algorithmically provides almost no benefit. Our main proof technique combines a novel coupling for suprema of random walks with arguments from queueing theory (this is joint work with Dmitriy A. Katz-Rogozhnikov, Yingdong Lu, Mayank Sharma, and Mark S. Squillante from IBM T.J. Watson Research Center).