2016 INFORMS Annual Meeting Program

MA37

INFORMS Nashville – 2016

MA37 205C-MCC Securing Sustainable Future Sponsored: Manufacturing & Service Oper Mgmt, Sustainable Operations Sponsored Session Chair: Elena Belavina, University of Chicago Booth School of Business, Chicago, IL, United States, elena.belavina@chicagobooth.edu 1 - Grocery Access Market Structure And Food Waste Elena Belavina, University of Chicago, elena.belavina@chicagobooth.edu Access to grocery, or how dense is the network of retail stores in a neighborhood, varies extensively as a result of zoning laws and other city government initiatives. Similarly, some markets are dominated by one chain, while others have a high degree of competition with a lot of independent grocery stores. This paper studies how access to grocery stores, and the extent and nature of competition in the grocery retail market influences food waste. 2 - Pricing, Product Display, Inventory And Waste Management For Deteriorating Products. Dorothee Honhon, University of Texas at Dallas, Richardson, TX, United States, dorothee.honhon@utdallas.edu Xiajun Amy Pan, Zumbul Atan We consider the problem of a retailer managing the inventory and the prices of products whose quality deteriorates over time. We show that by appropriately displaying the most/least fresh products on the store shelves, the retailer can, in some cases, increase profits and reduce waste. 3 - The Impact Of Legislation on Food Waste Worldwide, 30-40% of all food is wasted, which has a significant environmental impact: agriculture is responsible for 22% of all greenhouse gas emissions. This research explores whether California’s AB32 and renewable energy legislation (that exempts farmers from carbon tax) increases the negative environmental impact of the food system (by preventing the true cost of food to propagate down the supply chain making food waste relatively inexpensive). Further, we study how the supply chain structure and design contribute to food waste and strategies for mitigating this. 4 - Design Implications Of Extended Producer Responsibility For Durable Products Ximin (Natalie) Huang, Georgia Institute of Technology, 800 West Peachtree Street, NW, Atlanta, GA, 30308, United States, ximin.huang@scheller.gatech.edu, Atalay Atasu, Beril L Toktay We consider a monopolist who has two product design options to manage the end-of-life costs/revenues associated with its products: making products more durable or recyclable. We explore how the recyclability and durability choices are affected by the requirements of take-back legislation. MA38 206A-MCC Meet the Editors Panel – NPD, Innovation, and Technology Invited: New Product Development Invited Session Moderator: Sanjiv Erat, University of California-San Diego, UCSD, La Jolla, CA, United States, serat@ucsd.edu 1 - Meet The Editors Panel - NPD, Innovation, andTechnology Joel Wooten, University of South Carolina, 1014 Greene St., Columbia, SC, 29208, United States, joel.wooten@moore.sc.edu This interactive session aims at assisting readers and researchers in staying informed on the most important topics and the latest development in New Product Development, Technology, and Innovation Management. 2 - Panelist Cheryl Gaimon, Georgia Institute Of Technology, Scheller College Of Business, Atlanta, GA, 30308, United States, cheryl.gaimon@scheller.gatech.edu 3 - Panelist Moren Levesque, York University, Schulich School Of Business, Toronto, ON, Canada, mlevesque@schulich.yorku.ca Alexandra Heeney, Stanford University, Stanford, CA, 9, United States, aheeney@stanford.edu, Warren H Hausman, Erica Plambeck

MA39 207A-MCC Applied Probability and Machine Learning II Sponsored: Applied Probability Sponsored Session Chair: Sewoong Oh, UIUC, 2011 Savanna Dr, Champaign, IL, 61822, United States, sewoong79@gmail.com 1 - Online Rules For Control Of False Discovery Rate Adel Javanmard, Assistant Professor, University of Southern California, Bridge Memorial Hall, 3670 Trousdale Parkway, Los Angeles, CA, 90089, United States, ajavanma@marshall.usc.edu, Andrea Montanari Multiple hypothesis testing is a core problem in statistical inference and arises in almost every scientific field. A common error criteria in this context is the false discovery rate (FDR). In this talk, we consider the problem of controlling FDR in an “online manner”. Concretely, we consider an ordered, possibly infinite, sequence of null hypotheses where at each step the statistician must decide whether to reject current null hypothesis having access only to the previous decisions. We introduce a class of generalized alpha-investing procedures and prove that any rule in this class controls FDR in online manner. Time permitting, we will discuss applications for Ad click predictions and A/B testing. 2 - Newton Stein Method: An Optimization Method For Glms Murat Erdogdu, Stanford University, erdogdu@stanford.edu We consider the problem of efficiently computing the maximum likelihood estimator in Generalized Linear Models (GLMs) when the number of observations is much larger than the number of coefficients (n>>p>>1). In this regime, optimization algorithms can immensely benefit from approximate second order information. We propose an alternative way of constructing the curvature information by formulating it as an estimation problem and applying a Stein-type lemma, which allows further improvements through sub-sampling and eigenvalue thresholding. Our algorithm enjoys fast convergence rates, resembling that of second order methods, with modest per-iteration cost. 3 - Data-driven Rank Breaking For Efficient Rank Aggregation Ashish Khetan, UIUC, Urbana, IL, United States, Khetan2@illinois.edu Rank aggregation systems collect ordinal preferences from individuals to produce a global ranking. Rank-breaking is a common practice to reduce the computational complexity of learning the global ranking. The individual preferences are broken into pairwise comparisons and applied to efficient algorithm. However, naive rank-breaking approaches can result in inconsistent estimates. The key idea to produce accurate and unbiased estimates is to treat the pairwise comparisons unequally, depending on the topology of the collected data. In this paper, we provide the optimal consistent rank-breaking estimator. This allows us to characterize the trade-off between accuracy and complexity. 4 - On The Capacity Of Information Processing Systems Kuang Xu, Stanford University, Stanford, CA, United States, kuangxu@gmail.com, Laurent Massoulie We analyze a family of information processing systems, where a finite set of experts or servers are employed to extract information about a stream of incoming jobs, each associated with a hidden label. An inspection by an expert produces a noisy outcome that depends both on the job’s hidden label and the type of the expert, and occupies the expert for a finite time duration. A decision maker’s task is to dynamically assign inspections so as to accurately recover all job labels while keeping the system stable. Crowdsourcing, diagnostics and experiment designs are among our chief motivations. Our main result is an asymptotically optimal inspection policy that utilizes the fewest experts.

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