Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

SA16

3 - Optimal Practice Processes for Performance Guillaume Roels, INSEAD, Boulevard de Constance, Fontainebleau, 77305, France

n SA16 North Bldg 127B Electricity Demand Side Management Sponsored: Manufacturing & Service Oper Mgmt/Sustainable Operations Sponsored Session Chair: Ali Fattahi, University of California-Los Angeles, Los Angeles, CA, 90095, United States 1 - Demand Response Planner for Building Districts Juan Alejandro Gomez-Herrera, Polytechnique Montreal, Montreal, QC, Canada, Miguel F. Anjos, Luce Brotcorne We present a demand response planner for a district with heterogeneous buildings. This approach allows to aggregate a large number of end-users by identifying and selecting power capacity profiles. The user engagement combined with storage and local generation resources allows to provide demand response services to the grid operator. We use a multi-objective optimization model to trade off the total cost of energy consumption and the user’s dissatisfaction generated by load shifting. Computational experiments validate the performance of the proposed approach. 2 - A Computational General Equilibrium Model for Power Interruption Contracts Lakshmi Palaparambil Dinesh, Purdue Fort Wayne, Fort Wayne, IN, United States Demand Response (DR) is reduces consumer electricity bills and energy consumption.There are several models incorporating DR technology into customer bill reduction models. Our model focuses on large scale mixed integer linear programming. In this paper, we plan to look at a DR customer bill reduction when there are back up storage devices such as batteries or solar photo voltaic cells available to the customer. We explore three possible scenarios (i) Does the customer bill reduce further when there are batteries/solar as well as DR? (ii) If there is a reduction, how sizable is that reduction? (iii) How do the solution times change when back up storage is included in the model? 3 - That’s Not Fair: Tariff Structures for Electricity Markets with Rooftop Solar Siddharth Prakash Singh, Carnegie Mellon University, Tepper School of Business, 5000 Fobes Avenue, Pittsburgh, PA, 15213, United States, Alan Scheller-Wolf Increased penetration of rooftop solar has led to decreased utility profitability and undesirable cross-subsidization among customers. Regulatory responses have been controversial; changes in Nevada induced SolarCity, the market leader in solar systems, to suspend operations. We show analytically that for a regulator to induce a socially desirable outcome, two tariff features are essential — the ability to discriminate among customer tiers and the ability to discriminate between solar and non-solar customers. We present a tariff, featuring full retail price repurchasing from residential solar customers with these features. We use data from Nevada and New Mexico to illustrate our findings. 4 - An Analysis of Demand Response Programs in the Wholesale Electricity Market Asligul Serasu Duran, Haskayne School of Business, University of Calgary, Calgary, AB, Canada, Baris Ata, Ozge Islegen We build a model to explore the participation and the compensation of demand response (DR) providers in the wholesale electricity market, motivated by the Federal Energy Regulatory Commission’s (FERC) order that authorized DR resources to receive the same market clearing prices that generating resources receive. We consider alternative compensation schemes for DR providers, and explore the changes in the investment decisions, electricity prices, generators and DR providers’ profits, and consumer welfare. 5 - Peak Load Energy Management by Direct Load Control Contracts Ali Fattahi, University of California-Los Angeles, Anderson School of Management, B501, Los Angeles, CA, 90095, United States, Sriram Dasu, Reza Ahmadi We study peak load energy management by direct load control contracts (DLCCs) that utilities use to curtail electricity consumption of the participating customers during peak load periods. These contracts stipulate a limit on the number of times (calls) and the total number of hours of power reduction per customer as well as the duration of each call. This is a provably difficult (NP-hard) optimization problem. We develop an approximation scheme and analyze its asymptotic behavior. We show that the relative error approaches zero as problem size (length of the horizon) approaches infinity. We apply our solution approach to the data provided by three major utility companies in California.

Throughout their lifetime, people engage in many activities to learn new skills or develop their abilities. Although endurance sports training, motor learning, and cognitive learning have their own idiosyncrasies, they can all be viewed as processes of repeated practice to increase performance. Yet, there exist few guidelines to optimize such processes. Building upon research in endurance sports training and learning, this paper proposes a behavioral model of a practice process and optimizes it to maximize performance on a predefined date. We demonstrate the optimality of distributing practice over time, of tapering, and of periodization. 4 - Quality and Product Cycles in Fast Fashion Xiaoyang Long, University of Wisconsin-Madison, Wisconsin School of Business, 975 University Avenue, Madison, WI, 53706, United States, Javad Nasiry A “fast fashion business model allows firms to react quickly to changing consumer trends by introducing new products. We study the effect of this business model on a firm’s new product introduction frequency and product quality decisions when consumer taste changes over multiple periods. n SA15 North Bldg 127A Appointment and Capacity Planning in Health Care Sponsored: Manufacturing & Service Oper Mgmt/Service Operations Sponsored Session Chair: Itai Gurvich, Cornell University, New York, NY, 10044, United States Co-Chair: Benjamin Grant, Kellogg School of Management, Evanston, IL, 60201, United States 1 - Managing Appointment Booking Under Customer Choices Nan Liu, Boston College, 140 Commonwealth Avenue, Fulton Hall, Room 340, Chestnut Hill, MA, 02467, United States, Peter Van de Ven, Bo Zhang Motivated by the increasing use of online appointment booking platforms, we study how to offer appointment slots to customers in order to maximize the total number of slots booked. We develop two models, non-sequential offering and sequential offering, to capture different types of interactions between customers and the scheduling system. In these two models, the scheduler offers either a single set of appointment slots for the arriving customer to choose from, or multiple sets in sequence, respectively. Given the ongoing growth of online and mobile appointment booking platforms, our research findings can inform user interface design of these booking platforms. 2 - The Zocdoc Effect: How Does Online Information Impact Appointment Availability in Outpatient Care? Yuqian Xu, University of Illinois at Urbana-Champaign, Wohlers Hall 487, 1206 S. 6th St, Champaign, IL, 61820, United States, Mor Armony In this paper, we propose a queueing model to study the impact of online information on doctor’s service decisions. We characterize the equilibrium strategy of the doctor, and show the impact of market size on the equilibrium strategy. 3 - Optimal Dynamic Appointment Scheduling of Base and Surge Capacity Benjamin Grant, Kellogg School of Management, 1881 Oak Avenue, # 1307W, Evanston, IL, 60201, United States, Itai Gurvich, Jan A. Van Mieghem, R. Kannan Mutharasan We study dynamic stochastic appointment scheduling when delaying appointments increases the risk of incurring costly failures, such as readmissions in health care or engine failures in preventative maintenance. When near-term base appointment capacity is full, the scheduler faces a trade-off between delaying an appointment at the risk of costly failures versus the additional cost of scheduling the appointment sooner using surge capacity.

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