Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WC49

n WC49 North Bldg 230 Energy Policy and Planning III Contributed Session Chair: Cristiana L. Lara, Carnegie Mellon University, 238 46th Street, Pittsburgh, PA, 15201, United States 1 - Joint Benefit of Transmission Switching, Siting, and Sizing of Energy Storages in Power Systems Meltem Peker, Research Fellow, Bilkent University, Department of Industrial Eng, Ankara, Turkey, Ayse Selin Kocaman, Bahar Kara This study discusses the joint benefits of transmission switching and other control mechanisms such as energy storage systems, demand side management and renewable energy curtailment for using clean sources in electricity generation without endangering the system. We analyze the effect of transmission switching on the total investment and operational costs, sitting and sizing decisions of energy storage systems, and changes in the load-shedding and renewable energy curtailment amounts by using an extensive computational study. 2 - Undetectable Cyber Physical Attacks on Power Grids under the AC Model Mauro Escobar, Columbia University, New York, NY, 10027, United States, Daniel Bienstock We describe an algorithm for computing undetectable cyber-physical attacks on power grids under the AC power flow model. An adversary attacks a small set of nodes of the network: it can modify their demands as well as hide the signals that are measured (voltage and current). These actions are calculated so as to hide the underlying truth, which includes severe equipment overloads, while remaining consistent (i.e. not noticed) from the perspective of the control center of the system. On a second stage, we provide a mechanism to detect the attacked zone. We provide an algorithm and run experiments on large grids. 3 - Triple-bottom-line Approach to Optimizing Electricity Demand Response Schemes Using Smart Meter Data Electricity Demand Response (DR) schemes impact people, planet, and profit. They can help low income consumers benefit from low cost of tariffs during the off-peak hours; reduce CO2 emissions by shifting the load to hours that solar and wind contribute more to power generation; and elongate the life of electricity distribution assets by reducing the peak-hour shocks. We use a three-objective optimization model to estimate the optimum relocation of consumption loads during off-peak/shoulder/peak hours. We analyze smart meter data supplied by Eandis-Belgium to estimate model parameters and provide decision makers with Pareto-efficient solutions utilized in power distribution command centers. 4 - Policy Making for Microgrid Planning to Reduce Emission Aida Khayatian, University of Houston, Houston, TX, United States, Masoud Barati, Gino J. Lim Integrated resource planning is intended to appraise new energy resources that examine a full spectrum of alternatives to enhance power system. The competitiveness of power investors, environmental issues, and reliability are challenges faced by power system planners. Future load growth, power output, and power outage in the face of uncertainty are other obstacles. This study integrates microgrid (MG) designing and expansion planning with generation and transmission planning to study the potential advantages of MG. Some performance indices are proposed to establish policy. The case studies illustrate the application of proposed model and policy. 5 - Stochastic Dual Dynamic Integer Programming for Electric Power Infrastructure Planning Cristiana L. Lara, Carnegie Mellon University, Pittsburgh, PA, 15213, United States, Benjamin Omell, David Miller, Ignacio E. Grossmann We address the long-term planning of electric power infrastructure under uncertainty. We propose a multi-stage stochastic integer programming formulation that optimizes the generation expansion to meet the projected electricity demand over few decades while considering detailed operational constraints, intermittency of renewable generation, power flow between regions, and load demand uncertainty. To solve the large-scale model, we decompose the problem using Stochastic Dual Dynamic Integer Programming (SDDiP), incorporate scenario sampling, and solve in parallel nodes within the same stage. We report results for the region managed by the Electric Reliability Council of Texas. Amir-Behzad Samii, Professor, Vlerick Business School, Bolwerklaan 21, Brussels, 1210, Belgium, Olga Varganova

n WC50 North Bldg 231A Retail Management Contributed Session Chair: Armagan Bayram, University of Michigan Dearborn, Livonia, MI, 48152, United States 1 - Channel Transparency and Omnichannel Retailing: The Impact of Sharing Retail Store Inventory Availability with Online Shoppers Xinyi Ren, University of Maryland, 3330 Van Munching Hall, College Park, MD, 20742, United States, Philip Evers This paper empirically examines the effects of sharing retail store inventory availability with online shoppers at both the marketing and reverse logistics interfaces. Specifically, industry data is collected from a leading North American retailer to answer the following research questions 1. How does sharing brick- and-mortar inventory availability affect customer purchasing decisions at online and offline channels? 2. How does this policy affect customer conversion rates at the online and offline channels and the operational costs associated with product returns? Furthermore, the implications of these findings on inventory management are discussed. 2 - Food Waste in Online versus Offline Grocery Shopping Alwin Dsouza, Arizona State University, 6459 S. Essex, Mesa, AZ, 85212, United States, Lauren Chenarides, Timothy Richards U.S. households are responsible for a significant portion of food waste, which results when shoppers are unable to match purchases to expected consumption. Using multichannel store scanner data, this study investigates how the amount of food waste varies across online, offline and mixed shoppers. While online shoppers are more inclined to follow a shopping list, online shoppers are often required to pay a delivery fee and follow a minimum basket size. We use a model of consumer learning and inventory behavior to explore these two opposing effects and their impact on household-level food waste. 3 - A Model for Fresh Produce to Jointly Optimise Shelf Space Allocation, Inventory, and Pricing Decisions Hasmukh Gajjar, Associate Professor, Indian Institute of Management Indore, Faculty Office #C-208, IIM Indore, Prabandh Shikhar, Rau-Pithampur Road, Indore, India, Bhavin J. Shah Fresh produce’s demand primarily depends on its displayed stock, freshness and price. We present a model to jointly arrive at shelf space allocation, inventory and pricing decisions. Numerical results and sensitivity analysis are carried out to test the usefulness of the model. 4 - Direct and Wholesale Price Optimization in Omnichannel Environment Using Bilevel Optimization Model Vishal Gupta, Indian Institute of Technology-Kharagpur, Department of Industrial & Systems Enggn., I. I T. Kharagpur, Kharagpur, 721302, India, Shrinath Dakare, Manoj Kumar Tiwari We considered multi-period price optimization problem for a manufacturer (leader), also having a direct channel, and a multi-location multi-channel retailer (follower). Both manufacturer and retailer try to maximize their profits; moreover, manufacturer tries to increase the market share of their product. Assuming price and delivery lead time dependent attraction function, location- based holding and fulfillment costs, we propose a bilevel model that has a multi-objective upper level and single objective lower level. In the resulting omnichannel environment, we demonstrate how the model is effective in setting wholesale and direct channel prices using intelligent search heuristic. 5 - Dynamic Pricing Under Customer Review Effect Ruizhi Shi, University of Minnesota, 1400 S. 2nd St, Minneapolis, MN, 55454, United States In this talk, we consider a monopolist selling a single product to a sequence of customers. Each customer will make a purchase decision base on the current review and the price. If a customer purchases the product, he will post a review, which is drawn from a normal distribution centered at the true quality q. Only the seller knows the true quality therefore the customers have to use the review as an estimation of the true quality. We derive the optimal policy on how the seller should adjust the price to maximize the expected revenue. We also derive upper bounds on the best performance of any policy. 6 - Order Fulfillment Policies for Ship from Store Implementation in Omni Channel Retailing Armagan Bayram, Assistant Professor, University of Michigan- Dearborn, 4901 Evergreen Road, Dearborn, MI, 48128, United States, Bahriye Cesaret We consider an omni-channel retailer having both online and store operations and implementing ship-from-store fulfillment model. In this model, store orders are fulfilled from store inventories, but for an online order, the retailer can ship it either from the online distribution center or from any store location that maximizes its overall profit. We investigate dynamic fulfillment decisions: from which location to fulfill an online order when it arrives. We incorporate the uncertainty both in demand and in the cost of shipment to individual customers. We develop a stochastic dynamic framework and present our analytical and numerical findings on optimal fulfillment strategies.

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