Naval Research Logistics: Special Issue on Online and Offline Learning in Operations Management
Guest Editors:
George Shantikumar, Purdue University (shanthikumar@purdue.edu)
Cong Shi, University of Michigan (shicong@umich.edu)
With the advent of explosive growth in data and computation power, prescriptive learning algorithms (both online and offline) have allowed large organizations to scale in ways that were not possible even a few years ago, e.g., Google search and advertising algorithms, Amazon recommender systems, Uber ridesharing matching and pricing algorithms, UPS vehicle routing algorithms. These judiciously designed algorithms are thus a critical component of businesses, and there is little doubt that almost all the business insights and decisions of tomorrow will be data-driven. This Special Issue seeks to publish papers that leverage online and offline learning algorithms to (i) derive effective learning solutions to business problems, or (ii) develop new learning methods associated with the integration of data and models in decision problems. To be considered, papers should examine significant decision-making problems in any of the application areas represented by Operations Management such as supply chains, revenue management, healthcare, service operations, marketing, fintech, including-but not limited to- inventory control, vehicle routing, supply chain networks, dynamic pricing, assortment optimization, online advertising, product rankings, recommendations, healthcare operations, medical decision-making, clinical trials, experimental design, queueing controls, and others.
Some possible topics include, but are not limited to, the following:
- Online and offline algorithms for inventory control, routing, supply chain optimization
- Online and offline algorithms for pricing, assortment, ranking, recommendations
- Online and offline algorithms for two-sided markets, sharing-economy
- Online and offline algorithms for service systems, queueing control
- Online and offline algorithms for healthcare operations, medical decision-making
- Online and offline algorithms for emergent application domains, e.g., blockchains
This list is not intended to be exhaustive. Authors are welcome to contact the editors for feedback on the suitability of topics.
Timeline:
Submissions open: May 1, 2022 to May 31, 2023
First-round decisions: September 30, 2023
Revise-and-resubmit deadline (if invited): December 31, 2023
Final decisions: March 31, 2024
Instructions:
Please submit your paper online at https://wiley.atyponrex.com/journal/NAV. Include suggestions for AEs and referees. NRL encourages succinct and clear writing, but there are no page limits. Also, papers may include a full-length appendix.
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Cong Shi
Associate Professor
Industrial and Operations Engineering
University of Michigan
Ann Arbor, MI
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