Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MA78

3 - Performance Evaluation of Geometric Serial Lines with Residence Time Constraints Feifan Wang, Arizona State University, 669 S. Mill Ave, Tempe, AZ, 85281, United States, Feng Ju Residence time constraints are commonly required in production systems, where parts need to stay in each buffer for some time within a predefined range. Due to a large state space, the direct analysis of such production systems is difficult. To address this problem, we develop an approximate model for a two-machine-one- buffer sub-system. An aggregation method, which takes the sub-system as a building block, is proposed to obtain the performance measures of a multi- machine line. Numerical experiments suggest that the approximate method can capture the system performance in both transient and steady state. 4 - Real-time Scheduling of Complex Resource Allocation Systems through Fluid Relaxations Spyros Reveliotis, Georgia Institute of Technology, 765 Ferst Drive ISyE, Atlanta, GA, 30332-0205, United States, Michael Ibrahim This work addresses the problem of the efficient real-time management of resource allocation in complex workflows that involve blocking and deadlocking effects. To this end, we adapt to the considered problem setting the scheduling approach that is based on the formulation and solution of a pertinent “fluid relaxation” of the addressed operations. Our results are substantially empowered by our ability to develop efficient deadlock avoidance policies for the considered resource allocation, that take the form of linear inequalities imposed on the underlying system state. Extensive numerical experimentation reveals the operational and computational efficiency of the derived policies. 5 - An Introduction to Framework of Simulation Analytics for Real-time Optimal Decision on What-if Scenarios Haobin Li, National University of Singapore, 1 Engineering Drive 2, Singapore, 117576, Singapore, Xiao Jin, Weizhi Liu, Chenhao Zhou, Loo Hay Lee, Ek Peng Chew A concept of simulation that supports a real-time decision making has raised much attention in recent years. However, it remains unclear how to combine simulation with an online decision in a valid way. To categorize main issues and pave a way for a possible application, we propose a new framework, namely “Simulation Analytics” that can be treated as an interface between simulation and real-time decision process. We expect such a paradigm to be universal in the new era for simulation-based optimization. A literature study is first conducted followed by a demonstration of the full framework. A brief case study is attached at the end which hints a possible application under this frame. n MA77 West Bldg 213A Location Models III Sponsored: Location Analysis Sponsored Session Chair: Pawel J. Kalczynski, CSU-Fullerton, 800 N. State College Blvd., Fullerton, CA, 92834-6848, United States 1 - Self-organized Carpools with Meeting Hubs Pawel J. Kalczynski, California State University-Fullerton, 800 N. State College Blvd., Fullerton, CA, 92834-6848, United States, Malgorzata M. Miklas-Kalczynska We incorporate optional meeting hubs into the original car pooling problem. A meeting hub is a common origin for all carpool participants. It may be one of the participants’ origins or a chosen meeting point such as a plaza or gasoline station. We present a new heuristic, formulated and tested on real-world and simulated car pooling problem instances, that mimics a decentralized carpool self- organization process by allowing commuters to maximize their own savings. Our findings reveal system-wide savings similar to centralized models, and a potential strategy for improving carpool utilization. 2 - Cooperative Cover of Uniform Demand Zvi Drezner, California State University Fullerton, Steven G. Mihaylo College of Business and Economics, Dept of ISDS, Fullerton, CA, 92834, United States, Tammy Drezner We investigate the total covered area by multiple facilities applying the cooperative cover model. The cooperative cover area is much larger than the one found by standard cover models. We also show that for a large number of facilities located in a symmetric grid, an hexagonal grid is best. We also investigated covering a given area by a given number of facilities, such as a square, with the weakest possible signal emitted by the facilities.

3 - A Voronoi Based Heuristic for the Planar Multiple Obnoxious Facilities Location Problem Pawel J. Kalczynski, California State University-Fullerton, 800 N. State College Blvd., Fullerton, CA, 92834-6848, United States, Zvi Drezner, Said Salhi Consider a situation in which a given number of facilities must be located in a convex polygon with the objective of maximizing the minimum distance between facilities and a given set of communities subject to the facilities being farther than a certain distance from one another. This continuous multiple obnoxious facility location problem is very difficult to solve by commercial nonlinear optimizers. We propose a mathematical formulation of two variants of the problem and a heuristic approach based on Voronoi diagrams and a binary linear program. We found that our results are much better and were obtained in a fraction of the time required by other popular state of the art solvers 4 - Advances in Competitive Facilities Models Tammy Drezner, California State University Fullerton, 800 N. State College, Fullerton, CA, 92834, United States, Zvi Drezner, Dawit Zerom Two improvements to the Huff gravity model are proposed and tested. 1) Assuming that facilities’ attractiveness has a random distribution. Perception of facilities’ attractivenss vary among customers. 2) Assuming different decay functions for different facilities. In existing models the distribution of demand by distance has the same shape. However, more attractive facilities attract customers from larger distances. The decline in patronage is slower than the decline for less attractive facilities. n MA78 West Bldg 213B Joint Session PSOR/SOLA: Location Models for Social Good Sponsored: Location Analysis Sponsored Session Chair: Kayse Lee Maass, Northeastern University, 360 Huntington Ave, Boston, MA, 02115, United States 1 - Using Spatial Data Analytics to Identify Associations Between Home Healthcare Accessibility and Socioeconomic Factors Home healthcare can improve health outcomes and reduce healthcare costs, but only if the service is accessible. We use healthcare system and socioeconomic data to fit space-varying coefficient models, from which we make inference about spatially explicit relationships between home healthcare accessibility and socioeconomic factors including rural/urban status, income, and race/ethnicity. We find statistically significant and spatially varying relationships at the ZIP Code level in Arkansas. Our results suggest policies to address disparities and improve outcomes. 2 - Human trafficking: Barriers of Using Supply Chain Methodologies/Interdiction Models to Disrupt Illicit Supply Chains of Human Traffickers Felipe Aros-Vera, Ohio University, 277 Stocker Center, 1 Ohio University, Athens, OH, 45701, United States, Cami Jones, Alana Weszelits Human trafficking, specifically sex trafficking, is a form of modern day slavery that is occurring on a global scale and continues to gain foothold in the United States. This presentation maps the similarities of the sex trafficking supply chain to a standard supply chain framework and propose useful metrics specific to the sex trafficking supply chain. The main objective of this work is to provide foundational basis for future quantitative analysis on interdiction models to cripple sex traffic supply chains. 3 - A Broader Perspective: Integrating Societal Factors Into Human Trafficking Shelter Location Models Kayse Lee Maass, Assistant Professor, Northeastern University, Boston, MA, United States, Renata Alexandra Konrad, Andrew C. Trapp Rehabilitative shelters play a critical role in the safety, stabilization, and long term recovery of human trafficking survivors. Yet, in every U.S. state the demand for such shelters greatly exceeds the current capacity, and the lack of available, reliable data poses a challenge to human trafficking modeling. Using concepts from health and social welfare economics, we develop a decision analytic approach to maximize the societal value of locating additional shelters at the state level under budget constraints. We discuss our methods for quantifying societal factors and illustrate how the optimal placement of shelters is affected by changes to the budget, shelter costs, and societal benefits. Ashlea Bennett Milburn, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR, 72701, United States, Jessica Heier Stamm, Mehmet Serdar Kilinc

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