Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WC19

n WC18 North Bldg 128A Facilities Planning, Design, and Location Contributed Session Chair: Dnyaneshwar Mogale, Indian Institute of Technology, Kharagpur, Department of Industrial and Systems Engineer, Kharagpur, 721302, India 1 - Vertical Expansion a Solution for Future Container Terminals Nima Zaerpour, Assistant Professor, California State University- San Marcos, San Marcos, CA, 92096-0001, United States Container terminals play a major role in the growth of international trade. They need to accommodate the increasing number of containers while their space is limited, particularly close to major cities. One approach, often used in practice, is horizontal expansion through expensive land reclamation projects. In contrast, vertical expansion uses the available land more efficiently by storing containers in high-bay warehouses. In this paper, we study a next generation container terminal consisting of container storage towers. The results show that, compared to a traditional container block, the container tower can increase the annual throughput, while saving on the required footprint. 2 - A Lagrangean Decomposition Approach for Dynamic Block Stacking Planning Under Deterministic Demand Hueon Lee, PhD Candidate, University of Arkansas, 4207 Bell Engineering Center, 1 University of Arkansas, Fayetteville, AR, 72701, United States, Kelly Sullivan, John A. White In this research, the dynamic block stacking problem of determining which product lots to store in which storage row depths at each time epoch is considered for a block stacking storage system. The problem is formulated as an unsplittable multi-commodity flow problem based on a given layout of the system and known inventory cycles of product lots. To efficiently derive a good feasible solution to a large-scale instance, we propose a heuristics based on Lagrangean decomposition. It provides optimistic bounds of the optimal objective function value of the problem and generates feasible solutions using Lagrangean multipliers in an iterative process solving a Lagrangean dual formulation. 3 - A Neighborhood Search Heuristic for the P-Median Problem with Continuous Demand Shane Auerbach, University of Wisconsin-Madison, Madison, WI, United States, Rebekah Dix We develop a neighborhood search heuristic for the p-median problem with continuous demand. We discuss challenges to implementing the heuristic, propose solutions, and describe how it can be embedded in hybrid heuristics. We then apply the heuristic to computing optimal spatial allocations of facilities in US cities. In comparing these optimal allocations to the actual ones, we find that allocations of supermarkets do relatively poorly in minimizing transportation costs for consumers. 4 - Robust Emergency Relief Supply Planning Incorporating Evacuation Side Uncertainty Jyotirmoy Dalal, Assistant Professor, Indian Institute of Management Lucknow, Prabandh Nagar, IIM Road, Uttar Pradesh, Lucknow, 226013, India, Halit Uster We present an emergency response planning problem for foreseen disasters to supply relief by explicitly considering uncertainties in disaster location, intensity, duration, and evacuee-compliance. We present a robust optimization model that provides a decision maker with a choice of considering time-dependent or independent evacuation-related uncertainties. We devise a decomposition-based solution method for large-scale instances and conduct a case study to demonstrate the applicability of our approach. 5 - An Integrated Sustainable Food Supply Chain Network Design Model for Optimization of Strategic & Tactical Decisions Dnyaneshwar G. Mogale, Research Scholar, Indian Institute of Technology, Kharagpur, West Bengal, Kharagpur, 721302, India, Sri Krishna Kumar, Manoj Kumar Tiwari The developing countries are moving towards the modernized food supply chain system due to the growing population and post-harvest losses of food. In this study, a novel integrated multi-echelon, multi-period and inter-modal mathematical model is formulated to design the sustainable food grain supply chain network. The objective function of the model is to minimize the fixed cost of silo establishment, transportation, inventory and operational costs along with the cost of carbon dioxide emissions. The mathematical model is solved by using the CPLEX solver.

n WC19 North Bldg 128B Joint Session RMP/Practice Curated: Modern Applications of Revenue Management Sponsored: Revenue Management & Pricing Sponsored Session Chair: Maxime Cohen, NYU Stern, New York, NY, 10012, United States Co-Chair: Renyu Zhang, New York University Shanghai, Shanghai, 200122, China 1 - The Value of Personalized Pricing Michael Hamilton, Columbia University, New York, NY, United States, Adam Elmachtoub, Vishal Gupta Increased access to high-quality customer information has fueled interest in personalized pricing strategies, i.e., strategies that predict an individual customer’s valuation for a product and then offer them a customized price. While the appeal of personalized pricing is clear, it may also incur costs in the form of market research, investment in information technology, and branding risks. In light of these tradeoffs, in this work, we study the value of personalized pricing over simpler pricing strategies, and provide various closed-form upper bounds on the ratio that depend on simple statistics of the valuation distribution. 2 - Power of Monotonic Reoptimized Pricing in Revenue Management with Strategic Customers Yiwei Chen, University of Cincinnati, Cincinnati, OH, United States, Stefanus Jasin We study a canonical revenue management problem that a seller sells a single product with finite inventory over a finite horizon. Customers are forward looking who strategize their purchasing times. We propose a simple heuristic policy that requires the seller to repeatedly solve a simple static optimization problem by using the updated sales information. The price process is restricted to be non-decreasing over time. Thus, it incentivizes customers to behave myopically. We show that when the seller’s initial inventory and the length of the horizon proportionally grow large (scaled by k), the regret of our proposed policy is upper bounded by O (log k). 3 - Competition and Coopetition for Two-sided Platforms Renyu Zhang, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China, Maxime Cohen We study the two-sided competition between online service platforms. We develop a new approach to characterize the existence and uniqueness of equilibrium when platforms compete for both demand and supply. Armed with this result, we then investigate coopetition between different ride-sharing platforms by introducing new joint services. The coopetition between different platforms is through profit sharing contracts. Interestingly, we show that a well- designed profit-sharing contract can will benefit both platforms. In addition, we find that one can design a profit-sharing contract that also benefits riders and drivers. 4 - Electricity Pricing with Limited Consumer Response Saed Alizamir, Yale University, 206 Elm Street, P.O. Box 209052, New Haven, CT, 06520, United States, Shouqiang Wang, Fariba Farajbakhsh Retail electricity markets are characterized by nuanced features that distinguish them from mainstream retail settings. Specifically, the consumption quantity is influenced by factors not controlled by the consumer (e.g., weather), and consumption decisions can be readjusted on a continuous basis. In this paper, we study a monopolistic utility firm’s pricing decision in a retail electricity market. Using a rational inattention framework, we construct a demand model for consumers, whose consumption decisions demonstrate limited response to their ambient environment for a given price. Implications on social welfare and system reliability are drawn.

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