Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

SD11

2 - Mixed Integer Linear Programming Formulations for Resource Constrained Truck Scheduling in Cross Docks Pascal Wolff, Tongji University, Shanghai, China, Yongrui Duan, Hans-Christian Pfohl, Jiazhen Huo The number of articles on truck scheduling in cross-docks has been growing very fast in the last decades. However, many models are detached from industry practice since they do not explicitly consider resource constraints (e.g. available manpower, material handling equipment etc.). In this paper, we address this research gap and propose MILP formulations for truck scheduling in cross-docks that incorporate resource availability. Considering scarce resources that are required for cross-dock operations, these scheduling models meet industrial needs. Furthermore, we develop heuristic algorithms to tackle the problems. 3 - Capacity Planning and Production Scheduling for a Multi-facility Production System Nourah Almatooq, Arizona State University, Tempe, AZ, United States, Ronald G. Askin, Greg Gruber We investigate the integrated medium-range capacity planning and production scheduling problem for a multi-facility system producing multiple products with significant capacity change, semi-fixed and variable labor, shortage and logistics costs. We find the optimal production quantities, shift schedules, processing rates, overtime, inventory policy and shipments to demand markets to minimize system costs over the multiperiod planning horizon. Strategies for capacity modification to match dynamic demand are determined. 4 - A Novel Continuous-time Model for the Resource-constrained Project Scheduling Problem RCPSP Norbert Trautmann, University of Bern, FM Quantitative Methoden, Schuetzenmattstrasse 14, Bern, 3012, Switzerland, Adrian Zimmermann The widely studied resource-constrained project-scheduling problem RCPSP consists of determining the start times for a set of precedence-related project activities requiring time and scarce resources during execution such that the total project duration is minimized. We present a novel continuous-time MILP model which outperforms various state-of-the-art models in particular when the resource capacities are very scarce. n SD11 North Bldg 125B Socially Responsible and Demand-driven Operations Management Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session Chair: Muge Yayla Kullu, University of Central Florida, Orlando, FL, 32816, United States 1 - Nowcasting Restaurant Hygiene using Online Reviews Shawn Mankad, Cornell University We provide evidence for how information from online reviews of restaurants can be effectively used to identify cases of hygiene violations in restaurants, even after the restaurant has been inspected and certified. We use data from restaurant hygiene inspections in New York City from the launch of an inspection program from 2010 to 2016, and combine this data with online reviews for the same set of restaurants. Using machine learning techniques, we identify systematic instances of moral hazard, wherein restaurants with positive hygiene inspection scores are seen to regress in their hygiene maintenance within 90 days of receiving the inspection scores. 2 - Product Design and Pricing in Integrated Repair Supply Chain Honggang Hu, University of Florida, Gainesville, FL, 32611, United States, Avinash Geda, Vashkar Ghosh, Asoo J. Vakharia Firms are producing highly integrated products which are less repairable by third party repair firms. While firms lose out on consumers who value repairable products, they offer the firms a source of repair service revenue downstream. We address the issue where the firms faces trade-off between product design and potential revenue from repair services. 3 - Sustainable Management with a Triangle Sustainable Framework: Cases of Sustainable Manufacturing Yong Yin, Doshisha University, Karasuma-Imadegawa, Kamigyo-ku,, Kyoto, 602-8580, Japan, Kathryn E. Stecke, Dongni Li Triple bottom line is extended to a triangle sustainable framework that consists of categories of primary performance measures and drivers that address the relationships among the economic, environmental, and societal sustainable dimensions. Manufacturing cases of seru production are used to show that following particular practices and performance goals (e.g., pursuing responsiveness) naturally lead to sustainable outcomes. Our results are counter to the literature that claims that giving highest priority to the economic dimension makes it difficult to realize sustainability. A causal loop is used to identify sustainable drivers that induce a seru system to deliver sustainable goals.

4 - Recyclability of Post-disaster Debris Andriy Shapoval, Georgia Institute of Technology, Atlanta, GA, United States, Pinar Keskinocak, Beril Toktay This work investigates trade-offs in efforts to recycle debris after natural disasters. Various policies and interests of involved stakeholders may impact the possibility of creating efficient recycling programs. We evaluate the conditions under which recycling is viable across three dimensions: economic, environmental, and social. 5 - Reining in Onion Prices by Introducing a Vertically Differentiated Substitute Muge Yayla Kullu, University of Central Florida, 4000 Central Florida Blvd., Orlando, FL, 32816, United States, Omkar D. Palsule-Desai, Srinagesh Gavirneni Onion is an indispensable ingredient of the Indian diet and plays a vital role in the Indian economy, society, and politics. In this paper, we are interested in examining underlying causes of the onion price volatility that leads to significant social unrest in the country. We identify conditions under which (i) it is optimal to introduce the processed produce as a vertically differentiated substitute to the fresh produce; and (ii) the processed produce should be managed by cooperatives instead of private firms. Our model captures (i) competition between non-profit and for-profit organizations, (ii) consumers’ valuation discount for processed produce, and (iii) perishability of the fresh produce. Chair: Meinolf Sellmann, Cortlandt Manor, NY, 10567, United States 1 - A Hybrid Decision Diagram and Mixed-integer Programming Approach for Optimization Jaime E. Gonzalez, Polytechnique Montreal, Montreal, QC, Canada, Andre Augusto Cire, Andrea Lodi, Louis-Martin Rousseau We present an optimization framework which integrates binary decision diagrams (BDDs) and mixed-integer programming (MIP) technology. In the proposed framework, a relaxed BDD plays the role of a search tree by identifying parts of the search space that can be efficiently explored by solving MIP models associated with the nodes of the BDD. Conversely, the MIP model results are iteratively employed to further refine the BDD and find primal bounds. Selecting the BDD nodes to explore by MIP highly impacts the approach’s performance and then, the integration of supervised learning can be critical for this purpose. We present computational experiments on the maximum stable set problem. 2 - Maximizing the Expected Value of Order Statistics, with an Application to Sports Betting Pools David Bergman, University of Connecticut, Storrs, CT, United States, Carlos H. Cardonha, Jason P. Imbrogno, Leonardo Lozano Real-world optimization problem often require maximizing the expected value of order statistics. We discuss algorithms for solving this general and complex class of optimization problems, and describe how they can be applied to optimally selecting entries in sports betting pools. 3 - Predictive and Prescriptive Analytics for Location Selection of Add-on Retail Products Teng Huang, University of Connecticut, Storrs, CT, 06268, United States, David Bergman, Ram Gopal In this paper we study a predictive-and-prescriptive analytics framework for optimizing expansion decisions for retailers selling add-on products. We build predictive models for understanding the derived demand of the add-on product and establish an optimization framework for automating expansion decisions to maximize expected sales. n SD12 North Bldg 126A Using Estimated Data in Optimization Emerging Topic: OR Frontiers Emerging Topic Session

94