2015 Informs Annual Meeting

SC05

INFORMS Philadelphia – 2015

SC04 04-Room 304, Marriott Gender Inspired Research Sponsor: Women in OR/MS Sponsored Session Chair: Margret Bjarnadottir, Assistant Professor of Management Science and Statistics, Robert H. Smith School of Business, University of Maryland, 4324 Van Munching Hall, College Park, MD, 20742, United States of America, margret@rhsmith.umd.edu 1 - Innovative Pedagogical Interventions to Increase Retention of Women in Engineering Susana Lai-yuen, Associate Professor, University of South Florida, 4202 East Fowler Avenue, ENB 118, Tampa, FL, 33620, United States of America, laiyuen@usf.edu, Grisselle Centeno This work addresses the broad challenge of identifying practices and developing resources to help overcome evident gender equity issues in science and engineering education. Specifically, a set of pedagogical resources focused on healthcare systems and OR applications have been developed. Experiences related to development, implementation and outcomes will be discussed. 2 - Bridging the Gap: Responses to Equal Pay Legislation David Anderson, Assistant Professor, Baruch, davidryberganderson@gmail.com, Margret Bjarnadottir We study how firms can reduce the estimated pay gap between men and women in the most cost efficient way. We show that by intelligently increasing workers’ wages who will have the greatest impact, we can meet the “Equal Pay for Equal Work” standard for less than half the cost of the naive method of increasing all female workers’ wages equally. We further explore the impacts of equal cost mandates on compensation, fairness and the implications of this work on outside verification parties. 3 - Work-Life Balance for Women Wendy Casper, The University of Texas at Arlington, Dept. of Management, Arlington, TX, United States of America, wjcasper@uta.edu, Victoria Chen Work-life balance is important to many women. Despite this, there is little agreement about what work-life balance is. This presentation discusses the notion of balance and identifies commonly held definitions of this concept, concluding with a few ideas about how women can gain a greater sense of balance in their lives. SC05 05-Room 305, Marriott Extracting Business Value from Social Media Analytics: Techniques and Applications Cluster: Social Media Analytics Invited Session Chair: Shih-Hui Hsiao, University of Kentucky, 550 S. Limestone, Lexington, KY, 40526, United States of America, shs222@uky.edu 1 - Who are the Opinion Leaders? A Relative Assessment of Opinion Leader Mining Algorithms Shih-Hui Hsiao, University of Kentucky, 550 S. Limestone, Lexington, KY, 40526, United States of America, shs222@uky.edu, Ram Pakath Several methods have been proposed in the Social Media Analytics literature for identifying Opinion Leaders (OL) in online social networks. In this talk, I will describe the design and implementation of, as well as preliminary findings from, an experiment that compares existing OL mining algorithms to one another in terms of solution speed and quality. This study is a prelude to a larger project that also seeks to improve upon extant procedures. 2 - Real-time Social Media Analytics in Health Care: Discovery Knowledge from Online Communities Yichuan Wang, Industrial & Systems Engr St, Department of Industrial and Systems Engineering, Shelby Center, Auburn University, Auburn, AL, 36849,yzw0037@auburn.edu, Yedurag Babu, Terry Byrd Dramatic changes in business environments have galvanized firms toward searching for external knowledge from social media to complement the insufficiency of organizational resource. However, in healthcare social media sources rarely have been analyzed and used to support medical decision making. This study proposes a real-time knowledge discovery framework to support effective exploration of knowledge which has been prototypically implemented on the base of Web data from healthcare communities.

4 - Spotting Anomalies in Cyber Physical Datasets: The Case of Mobility Data

Konstantinos Pelechrinis, Assistant Professor, University of Pittsburgh, 135 N. Bellefield, IS 717B, Pittsburgh, PA, United States of America, kpele@pitt.edu, Evangelos Papalexakis, Christos Faloutsos How can we discover latent patterns in heterogeneous CPSs datasets and classify them as anomalous or not without labeled data? We propose using tensors to model heterogenous data and obtain latent patterns. We then propose a generic data-driven method for classifying each of the obtained patterns as normal or not. The realization of our technique is domain-specific. We showcase our method by applying it on a mobility dataset that captures locations visited by users at different times. SC03 03-Room 303, Marriott Contemporary Scheduling Cluster: Scheduling and Project Management Invited Session, Chair: Joseph Y.T. Leung Distinguished Professor, New Jersey Institute of Technology, Department of Computer Science, University Heights, Newark, NJ, 07102, United States of America 1 - Improved Algorithms for Single Machine Scheduling with Release Dates and Rejections Kangbok Lee, York College, CUNY, York College, The City University of New York, Jamaica, NY, 11451, United States of America, klee5@york.cuny.edu, Cheng He, Joseph Leung, Michael Pinedo We consider bi-criteria scheduling problems on a single machine with release dates and rejections and both the makespan and the total rejection cost have to be minimized. We consider two scenarios: (i) minimize the sum of the makespan and the total rejection cost, and (ii) minimize the makespan subject to a bound on the total rejection cost. We summarize the results obtained in the literature and provide for several cases improved approximation algorithms and FPTASs. 2 - Integrated Production and Delivery on Parallel Batching Machines Kai Li, Associate Professor, Hefei University of Technology, 193 Tunxi Rd, Hefei, 230009, China, hfutlk@139.com, Joseph Leung, Zhao-hong Jia We consider an integrated scheduling problem of production and delivery on parallel patching machines. The company will earn a positive profit only if a job is delivered by its due date. A 3PL provider is used to deliver the jobs. The goal is to maximize the total profit. We show that the problem is solvable in polynomial time if the jobs have identical sizes, but it becomes unary NP-hard if the jobs have different sizes. We propose heuristics for NP-hard cases and analyze their performances. 3 - Minimizing Total Completion Time in Flow Shop with Machine Unavailability using Meta-heuristics Hairong Zhao, Associate Professor, Purdue University at Calumet, Dept. of Math, C. S, & Statistics, Hammond, IN, 46323, United States of America, hairong@purduecal.edu, Yumei Huo We consider flow shop scheduling subject to machine availability constraints. The objective is to find a schedule that minimizes total completion time. This problem is strongly NP-hard even if machines are always available. Simple bounds are derived to slightly speed up the elimination process of a branch-and-bound algorithm. Then we propose a meta-heuristic algorithm based on genetic algorithms. Computational results show that the proposed meta-heuristic performs effectively and efficiently. 4 - Application of MGSA for the Coordinated Scheduling Problem in a Two-Stage Supply Chain Jun Pei, Assistant Professor, Hefei University of Technology, 193 Tunxi Rd, Hefei, 230009, China, feiyijun198612@126.com, Xinbao Liu This paper investigates a products and vehicles scheduling problem in a two-stage supply chain, where jobs need to be processed on the serial batching machines of multiple manufacturers distributed in various geographic zones and then transported by vehicles to a customer. A modified gravitational search algorithm (MGSA) is proposed to solve the problem. In MGSA,Several improvement strategies and the batching mechanism DP-H are introduced.

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