Presented By: U-M Industrial & Operations Engineering
CANCELED Departmental Seminar (899): Ramamoorthi Ravi, Carnegie Mellon University
Models and Methods for Omni-channel Fulfillment
THIS EVENT HAS BEEN CANCELED.
SEE LINK ABOVE FOR REPLACEMENT EVENT.
Title:
Models and Methods for Omni-channel Fulfillment
Abstract:
Omni-channel retailing, the combination of online and traditional store channels, has led to the use of traditional stores as fulfillment centers for online orders. A key aspect of omni-channel fulfillment problems is the trade-off between cancellations of accepted online orders and profits; a riskier fulfillment policy may result in more online sales but also more cancelled orders.
In this talk, I will describe a stochastic model of the process leading to order cancellations for a single item so that retailers may find fulfillment policies that effectively use this information along with shipping costs between various locations. We describe iterative algorithms based on Infinitesimal Perturbation Analysis (IPA) that converge to optimal and locally optimal policies within certain flexible policy classes for the multiple-location version of this model, and show their empirical performance on simulations based on real data from a high-end North American retailer.
Time permitting, I will describe a related problem of maximizing revenues subject to a constraint on cancellations across a large portfolio of items and an approach to solving it. This talk is based on the dissertation of Jeremy Karp at CMU describing work carried out jointly with Prof. Sridhar Tayur (CMU) and Dr. Srinath Sridhar (Onera Inc).
Bio:
Dr. R. Ravi is Andris A. Zoltners Professor of Business, and Professor of Operations Research and Computer Science at Carnegie Mellon University.
Ravi received his bachelor's degree from IIT, Madras, and Master's and doctoral degrees from Brown University, all in Computer Science.
Ravi's research focuses on models, methods and applications of discrete optimization, and their applications in the intersection of business and technology. He served as area editor for "Operations Research" in charge of the discrete optimization area between 2012-2017. He has formerly served as associate editor in the ACM Transactions on Algorithms, Management Science, Networks and Journal of Algorithms. He has also served on several international program committees including as the program chair for the 2008 IEEE Foundations of Computer Science (FOCS) conference. Ravi has co-authored two books, over 130 publications, and has a h-index of over 50. His research has been supported by the U.S. National Science Foundation, Office of Naval Research, Microsoft, Yahoo and Google; He has so far supervised 18 doctoral theses and developed over half a dozen new graduate classes.
Ravi has been at the Tepper School of Business since 1995 where he served as the Associate Dean for Intellectual Strategy from 2005-2008. He was Chair of the Future Educational Delivery Committee that launched the online hybrid Tepper MBA in 2013. He was elected a Fellow of the INFORMS in 2017.
SEE LINK ABOVE FOR REPLACEMENT EVENT.
Title:
Models and Methods for Omni-channel Fulfillment
Abstract:
Omni-channel retailing, the combination of online and traditional store channels, has led to the use of traditional stores as fulfillment centers for online orders. A key aspect of omni-channel fulfillment problems is the trade-off between cancellations of accepted online orders and profits; a riskier fulfillment policy may result in more online sales but also more cancelled orders.
In this talk, I will describe a stochastic model of the process leading to order cancellations for a single item so that retailers may find fulfillment policies that effectively use this information along with shipping costs between various locations. We describe iterative algorithms based on Infinitesimal Perturbation Analysis (IPA) that converge to optimal and locally optimal policies within certain flexible policy classes for the multiple-location version of this model, and show their empirical performance on simulations based on real data from a high-end North American retailer.
Time permitting, I will describe a related problem of maximizing revenues subject to a constraint on cancellations across a large portfolio of items and an approach to solving it. This talk is based on the dissertation of Jeremy Karp at CMU describing work carried out jointly with Prof. Sridhar Tayur (CMU) and Dr. Srinath Sridhar (Onera Inc).
Bio:
Dr. R. Ravi is Andris A. Zoltners Professor of Business, and Professor of Operations Research and Computer Science at Carnegie Mellon University.
Ravi received his bachelor's degree from IIT, Madras, and Master's and doctoral degrees from Brown University, all in Computer Science.
Ravi's research focuses on models, methods and applications of discrete optimization, and their applications in the intersection of business and technology. He served as area editor for "Operations Research" in charge of the discrete optimization area between 2012-2017. He has formerly served as associate editor in the ACM Transactions on Algorithms, Management Science, Networks and Journal of Algorithms. He has also served on several international program committees including as the program chair for the 2008 IEEE Foundations of Computer Science (FOCS) conference. Ravi has co-authored two books, over 130 publications, and has a h-index of over 50. His research has been supported by the U.S. National Science Foundation, Office of Naval Research, Microsoft, Yahoo and Google; He has so far supervised 18 doctoral theses and developed over half a dozen new graduate classes.
Ravi has been at the Tepper School of Business since 1995 where he served as the Associate Dean for Intellectual Strategy from 2005-2008. He was Chair of the Future Educational Delivery Committee that launched the online hybrid Tepper MBA in 2013. He was elected a Fellow of the INFORMS in 2017.
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