Informs Annual Meeting 2017

TE59

INFORMS Houston – 2017

3 - The Optimization of a Municipal Solid Waste Management System Yan Zhang, Associate professor, Dalian Maritime University, No.1 Lingshui Road, Dalian, 116023, China, yan.zhang@dlmu.edu.cn, Hualong Yang In a waste management system, the location of proper facilities for treating waste is a sensitive issue that has often caused political and social tension. We study the problem of simultaneous design of a distribution network with central treatment facilities, transfer stations and sanitary landfills, and the coordination of waste flows within this network. In order to determine the number, sizes and locations of the solid waste management facilities, we formulate a mathematical model for the problem and propose a heuristic to solve large problems efficiently. Finally, we apply these models and algorithms for the development of a solid waste management system for a specific region in Dalian. 4 - Covering and Connectivity Constraints in the Block Layout Shortest Loop Design Problem Ardavan Asef-Vaziri, Professor, College of Business and Economics, Dept of Systems and Operations MGMT, 18111 Nordhoff Street, Northridge, CA, 91330-8378, United States, aa2035@csun.edu, Morteza Kazemi The shortest loop covering at least one edge of each workcenter in a facility layout is an instance of the GTSP. The optimal solution to this problem is a promising design for non-vehicle-based material handling. This formulation is usually embedded within the problem of the concurrent design of the loop and the I/O stations for vehicle-based material handling. The shortest loop provides an effective heuristic scheme to achieve prosperous and robust solutions for the design of the loop and stations. We review and compare covering constraints formulations, provide new insight into connectivity constraints, improve the model formulation and solution procedure, and report computational results. 362F Health Care, Other Contributed Session Chair: Ilgin Acar, Anadolu University, Eskisehir, Turkey, ipoyraz@anadolu.edu.tr 1 - Filling Current Healthcare Gaps: Thoughtful Application of Robust Parameter Design with Conditions-based Selection of Regression Estimators Kathryn Pegues, Student, Clemson University, 104 Hyde Lane, Clemson, SC, 29631, United States, kpegues@gmail.com Underlying assumptions for RPD modeling and process conditions should be taken into account when selecting a regression estimator for developing fitted models. If these assumptions are incorrect, then a direct use of estimates obtained has the potential to be problematic, and the results may be potentially catastrophic, particularly when applied to the healthcare field. This paper examines alternative approaches to regression estimation when the process data indicates that asymmetry or a high degree of process variability exists. The performance of select alternative regression methods is compared using Monte Carlo simulation and numerical analysis. 2 - How Does Government’s Willingness to Fund Influence the Level of Health Prepayment Ying Zhang, Southeast University, Nanjing, China, yingzhang@seu.edu.cn Significant prepayment is a crucial factor to ensure that all individuals have access to effective health care at affordable prices. The research question we address here is, does government’s willingness to spend more on health means higher prepayment rates in the health financing system? These questions are addressed in 34 OECD members over the 1995-2013 period. Our findings show that government’s willingness to pay on health increases both the level of total prepaid expenditure and public prepayment [social health insurance, tax-financed]. Our research also highlights that government’s willingness to fund is not systematically crowding out private prepaid plans. 3 - Developing an HPV Infection Risk Prediction Model and Self-assessment Tool for Young Adult Females Rachel Holmer, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR, 72701, United States, reholmer@uark.edu, Shengfan Zhang According to the Centers for Disease and Control Prevention (CDC), nearly one in four people are currently infected with Human Papillomavirus (HPV) in the United States. Although most people with HPV never experience symptoms, there is a risk of developing different types of HPV-related cancers after infection. These cancers and other related diseases result in almost $8 billion spent annually for treatment. This research seeks to create a risk prediction model with a focus on young adult females that will assist these individuals to estimate the risk of HPV infection based on demographic, life style, and sexual behavior factors. TE59

4 - Blockchain Application in Healthcare Supply Chain for Effective Recall and Outdates Management Raja Jayaraman, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates, raja.jayaraman@kustar.ac.ae, Nelson King Product Lifecycle Management in healthcare is a complex process due to significant factors such as volume, variety, information inaccuracy on procurement, trends in consumption, poor data quality. In this presentation, we explore the role and use of blockchain technology in integrating critical product information across various processes in healthcare supply chain. 5 - Risk Factors Affecting Work Related Musculoskeletal Disorders in a Manufacturing Company Ilgin Acar, Anadolu University, Ikieylul Campus, Faculty of Engineering, Eskisehir, 26555, Turkey, ipoyraz@anadolu.edu.tr, Nihal Erginel, Sura Toptanci Various risk factors including individual factors such as personal and anthropometric variables, physical work and psychosocial factors are used as predictors of Work-related musculoskeletal disorders (WMSDs). The aim of this study is to build fuzzy regression models to understand the relationship between WMSDs and risk factors, to estimate the injuries, and to assess individual’s risk levels. A designed survey is used to collect data in a manufacturing company and to measure the influences of risk factors on the musculoskeletal symptoms. As the risk factors can be defined by fuzzy regression models, it may be easy to minimize the effect of risk factors to prevent WMSDs to provide safe environments. 370A Education and Economic Policy-Making Sponsored: INFORMEd Sponsored Session Chair: Vanitha Virudachalam, Wharton School, OID, 3730 Walnut Street, 500 Jon M. Huntsman Hall, Philadelphia, PA, 19104, United States, vanitha@wharton.upenn.edu 1 - The Urban and Rural Income Gap in China Based on the Opportunity Inequality Xiufan Zhang, Harbin Engineering University, Harbin, China, zhangxiufan@hrbeu.edu.cn With the continuous improvement of economic, China’s income increases fast, but the income gap between urban and rural areas is grim. Gini-coefficient is widely used to measure inequality in the distribution. But the deeper consequences behind inequality are ignored, including policy, institutional and social and cultural opportunities,making the income gap last for long. The paper summarizes various indicators of income inequality,calculates the income gap between urban and rural areas in China and analye the specific influencing factors of opportunity inequality on income inequality.The paper finally put forwards some Countermeasures of Urban - rural Income Gap. 2 - Re-engineering Agricultural Extension Services: Perceptions’ Intrinsic Role in the Design Process Elizabeth Ayala-Medina, Graduate Student, University of Puerto Rico-Mayagüez, Mayagüez, Puerto Rico, elizabeth.ayala@upr.edu, Betzabé Rodriguez Yearning to uphold a service of quality and excellence that meets the needs of farmers, this study pretends to expand on the intrinsic nature of perceptions throughout the design process. Furthermore, validate the assertiveness of integrating farmers’ perception in the development of a tool that aids in their learning process. 3 - Optimizing Performance Pay in K-12 Education Vanitha Virudachalam, Doctoral Candidate, The Wharton School, 3730 Walnut Street, 500 Jon M. Huntsman Hall, Philadelphia, PA, 19104, United States, vanitha@wharton.upenn.edu, Sergei Savin, Matthew Steinberg We study performance-based contracts in a K-12 educational setting, where a local school district (the principal) contracts with teachers (the agents) to meet student performance goals. Teachers’ wages are partly determined by student performance on the end-of-the-year state achievement test. The level of student knowledge is not perfectly known prior to this test; the district may choose to reduce this uncertainty by administering an interim assessment at a cost. We model this setting using a dynamic principal-agent model with partially hidden states. We determine the optimal performance-based contract and testing schedule the school district should offer teachers. TE60

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