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X-WR-CALDESC:Events for IORA - Institute of Operations Research and Analytics
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DTSTART:20210101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20221206T100000
DTEND;TZID=Asia/Singapore:20221206T113000
DTSTAMP:20260505T124529
CREATED:20220812T034841Z
LAST-MODIFIED:20221205T061819Z
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SUMMARY:IORA Seminar Series - Mika Sumida
DESCRIPTION:Mika Sumida is an Assistant Professor of Data Sciences and Operations in the Marshall School of Business at the University of Southern California. Her research focuses on developing efficient\, provably good algorithms for revenue management and resource allocation problems\, with applications in the sharing economy\, online marketplaces\, and delivery systems. She holds a Ph.D. in Operations Research and Information Engineering from Cornell University\, and a B.A. from Yale University. Prior to her Ph.D.\, she spent two years working in operations consulting at Analytics Operations Eng.\, Inc. \n\n\n\nLink to Register \n(Hybrid session)\nhttps://nus-sg.zoom.us/meeting/register/tZctcuGvqDksE9HugB0-sYRJ-g5nksO-uEaG\n\n\nTitle\nRevenue Management with Heterogeneous Resources\n\n\nVenue\nBIZ 1 – 0204\n\n\nAbstract\nWe study revenue management problems with heterogeneous resources\, each with unit capacity. An arriving customer makes a booking request for a particular interval of days in the future. We offer an assortment of resources in response to each booking request. The customer makes a choice within the assortment to use the chosen resource for her desired interval of days. The goal is to find a policy that determines an assortment of resources to offer to each customer to maximize the total expected revenue over a finite selling horizon. The problem has two useful features. First\, each resource is unique with unit capacity. Second\, each customer uses the chosen resource for a number of consecutive days. We consider static policies that offer each assortment of resources with a fixed probability. We show that we can efficiently perform rollout on any static policy\, allowing us to build on any static policy and construct an even better policy. Next\, we develop two static policies\, each of which is derived from linear and polynomial approximations of the value functions. We give performance guarantees for both policies\, so the rollout policies based on these static policies inherit the same guarantee. Lastly\, we develop an approach for computing an upper bound on the optimal total expected revenue. Our results for efficient rollout\, static policies\, and upper bounds all exploit the aforementioned two useful features of our problem. We use our model to manage hotel bookings based on a dataset from a real-world boutique hotel\, demonstrating that our rollout approach can provide remarkably good policies and our upper bounds can significantly improve those provided by existing techniques.
URL:https://iora.nus.edu.sg/events/iora-seminar-series-mika-sumida/
CATEGORIES:IORA Seminar Series
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DTSTART;TZID=Asia/Singapore:20221209T140000
DTEND;TZID=Asia/Singapore:20221209T150000
DTSTAMP:20260505T124529
CREATED:20221201T075852Z
LAST-MODIFIED:20221201T080015Z
UID:16468-1670594400-1670598000@iora.nus.edu.sg
SUMMARY:DAO-IORA joint seminar: Ethan X. Fang
DESCRIPTION:Ethan X. Fang is an Assistant Professor of Biostatistics & Bioinformatics at Duke Medical School and affiliated with Decision Sciences of Fuqua Business School and Rhodes Information Initiative at Duke University. He works on different data science problems from computational and statistical perspectives. Before joining Duke\, he was an assistant professor of Statistics at Penn State. He got his PhD from Princeton University under the direction of Han Liu and Robert Vanderbei\, and got his Bachelor’s degree from National University of Singapore under the direction of Kim-Chuan Toh. His works have appeared at top venues in different areas such as statistics\, optimization\, machine learning\, and operations research. He received 2016 Best Paper Prize in Continuous Optimization for Young Researchers (1 paper selected in 3 years). \n  \n\n\n\nVenue \nBIZ1 – 0204\n\n\nLink to Register\nhttps://forms.office.com/r/WgcFdUQQYW\n\n\nTitle\nInference for Ranking Problems\n\n\nAbstract\nWe propose a novel combinatorial inference framework to conduct general uncertainty quantification in ranking problems. We consider the widely adopted Bradley-Terry-Luce (BTL) model\, where each item is assigned a positive preference score that determines the Bernoulli distributions of pairwise comparisons’ outcomes. Our proposed method aims to infer the general ranking properties of the BTL model. The general ranking properties include the “local” properties such as if an item is preferred over another and the “global” properties such as if an item is among the top K-ranked items. We further generalize our inferential framework to multiple testing problems where we control the false discovery rate (FDR) and apply the method to infer the top-K ranked items. We also derive the information-theoretic lower bound to justify the minimax optimality of the proposed method. We conduct extensive numerical studies using both synthetic and real data sets to back up our theory.\n\n\n\nYou may contact WONG Cecilia/TAN Dorothy at 6516 6225/6516 3067 for enquiries.
URL:https://iora.nus.edu.sg/events/dao-iora-joint-seminar-ethanfang/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20221213T100000
DTEND;TZID=Asia/Singapore:20221213T113000
DTSTAMP:20260505T124529
CREATED:20220812T035011Z
LAST-MODIFIED:20221211T084251Z
UID:15982-1670925600-1670931000@iora.nus.edu.sg
SUMMARY:IORA Seminar Series - Saif Benjaafar
DESCRIPTION:Saif Benjaafar is McKnight Presidential Endowed Professor and Distinguished McKnight University Professor at the University of Minnesota. He is Head of the Department of Industrial & Systems Engineering at the University of Minnesota\, where he also directs the Initiative on the Sharing Economy. He is a founding member of the Singapore University of Technology and Design where he served as Head of Engineering Systems and Design. He is the Editor in Chief of the INFORMS journal Service Science. He serves on the board of directors of Hourcar\, a social car sharing organization. His research is in the area of operations broadly defined\, with a current focus on sustainable operations and innovation in business models\, including sharing economy\, on-demand services\, and digital marketplaces. He is a Fellow of INFORMS and IISE. \n\n\n\nVenue \nBIZ 1 – 0304\n\n\nLink to Register \n(Hybrid session)\nhttps://nus-sg.zoom.us/meeting/register/tZEqdumsqTIqHdynlcuEWYlO-g6cmUD5yg1t\n\n\nTitle\nDimensioning and Pricing of Shared Vehicle Networks\n\n\nAbstract\nIn the first part of the talk\, we consider the problem of optimal fleet sizing (dimensioning) in an on-demand and one way vehicle sharing system. We leverage a property of closed queueing networks that relates the dynamics of a network with K items to one with K-1 items to obtain explicit and closed form lower and upper bounds on the optimal number of vehicles that are asymptotically exact. We use the bounds to show that buffer capacity (capacity in excess of the nominal load) can be expressed in terms of three explicit terms that can be interpreted as follows: (1) standard buffer capacity that is protection against randomness in demand and rental times\, (2) buffer capacity that is protection against vehicle roaming\, and (3) a correction term. We show that the capacity needed to buffer against vehicle roaming can be substantial even in systems with vanishingly small demand. In the second part of the talk\, give a fixed fleet size\, we consider the dynamic pricing in such a network and show that a static pricing policy that arises from solving a maximum flow relaxation of the problem guarantees a performance ratio of order 1- O(1/) where K is the number of vehicles. The approach used\, which leverages the same property of closed queueing networks used in the dimensioning problem\, is startingly simple and yields performance guarantees that are tighter than those previously obtained in the literature. Time permitting\, we will also discuss ongoing work that considers dimensioning and pricing in other settings with spatial queueing network features. \n  \n(The talk will draw on material from the following two papers: \nhttps://pubsonline.informs.org/doi/epdf/10.1287/mnsc.2021.3957\, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3998297 and \nhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4130757. \n 
URL:https://iora.nus.edu.sg/events/iora-seminar-series-saif-benjaafar/
CATEGORIES:IORA Seminar Series
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