Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MA51

3 - A Free Environmental Lunch? The Impact of Environmental Management Systems on Energy Efficiency Seongkyoon Jeong, Arizona State University, Tempe, AZ, United States, Lee Jaeseok This study employs novel panel data on energy efficiency obtained from 2,728 South Korean plants operating between 2001 and 2014. We find that the adoption of ISO 14001, the representative environmental management standard, decreases energy efficiency by approximately 4%. The results suggest two main mechanisms through which EMS adoption reduces energy efficiency: 1) the installation of additional facilities for environmental management and 2) intensified environmental management activities. These findings suggest that EMS adoption inevitably produces additional environmental cost. More importantly, we find that this additional cost can be reduced through organizational learning. 4 - Are Hazardous Substance Rankings Effective? Basak Kalkanci, Georgia Institute of Technology, Atlanta, GA, 30339, United States, Wayne Fu, Ravi Subramanian We empirically investigate the relationship between changes in the relative assessed hazard levels of chemicals and emissions reductions (including the use of source reduction and end-of-pipe treatment) by facilities that use these chemicals. We also examine the moderating effects of operational leanness - an attribute that prior studies have found to be associated with better environmental performance - in the setting wherein the relative assessed hazard levels of chemicals change over time. n MA49 North Bldg 230 Optimization and Systems Engineering Methods in Petrochemicals and Energy II Sponsored: Energy, Natural Res & the Environment/Natural Resources Petrochemicals Sponsored Session Chair: Yifu Chen, University of Wisconsin-Madison, Madison, WI, United States 1 - Infeasibility Resolution for Multi-purpose Batch Process Scheduling Apurva Samudra, Rockwell Automation, Austin, TX, United States, Yash Puranik, Nikolaos Sahinidis, Alexander B. Smith, Bijan Sayyar-Rodsari We present a systematic approach for infeasibility diagnosis focusing on scheduling problems. Our approach exploits the known structure of scheduling models to isolate interpretable infeasible sets of constraints. We demonstrate the power of the algorithm on infeasible instances of the Westenberger-Kallrath multipurpose batch process modeled using a state-task network (STN) representation. The methodology presented in the paper is able to successfully analyze the cause of infeasibility and provide recommendations for resolving it. We demonstrate how these insights and recommendations can be presented to scheduling operators in an intuitive manner. 2 - Accounting for the Automation System when Scheduling Chemical Plant Operations Blake C. Rawlings, The University of Michigan, Ann Arbor, MI, 48109, United States, Venkatachalam Avadiappan, Stéphane Lafortune, Christos T. Maravelias, John M. Wassick Scheduling of chemical plant operations often involves solving an optimization problem, e.g., to maximize throughput. An approximate plant model is typically used to address industrial-scale problems. This introduces the possibility that the resulting schedule is not actually feasible, i.e., it could not be executed in the plant. We present a method based on analyzing a detailed model of the plant’s automation system to detect such infeasible schedules. In this case, the scheduling problem can then be solved again with additional constraints to avoid the infeasible schedule. Symbolic model checking is used to perform the analysis of the detailed model. 3 - Mathematical Optimization Based Approaches for the Design of Materials in Energy Applications Chrysanthos Gounaris, Carnegie Mellon University, Doherty Hall 3107, Dept of Chemical Engineering, Pittsburgh, PA, 15213, United States, Christopher H. Hanselman, Natalie M. Isenberg Energy process systems rely on the performance of advanced materials that serve as catalysts of chemical reactions or as separators of chemical species. Many of these materials are crystalline in nature, and derive their functionality from the precise placement of atomic building blocks in well-defined lattice positions. In turn, this gives rise to a discrete design space that can be suitably modeled and explored as a mixed-integer optimization problem to identify materials that are nanostructured to perform optimally in given energy-related contexts. Several case studies towards the design of metallic and metal-oxide surfaces, nanoparticles and bulk materials are discussed.

4 - An MIP Model and Rolling Horizon Approach for Strategic Shale Gas Development Nathan D. Blandino, EQT Corporation, Pittsburgh, PA, United States, Markus Gustav Drouven In this work we address the long term shale gas development problem which involves determining the optimal development strategy for drilling and fracturing gas wells, and producing through a constrained pipeline system. The problem is formulated as a large-scale MIP with a solution strategy that decomposes the problem temporally through a rolling horizon approach in order to extend the overall planning horizon while yielding near optimal solutions. The model and solution approach were developed by the Optimization Engineering department at EQT Corporation, a shale gas developer and the largest producer of natural gas in the United States. Joint Session Practice/Analytics/Practice Curated: IAAA Winner Reprise: Northwestern University’s Marathon Data Visualization Drives Safety Sponsored: INFORMS Section on Practice (formerly CPMS) Sponsored Session Chair: Carrie Beam, University of Arkansas, Walnut Creek, CA, 94596, United States 1 - SAFE (Situational Awareness for Events): A Data Visualization System Karen Smilowitz, Northwestern University, Industrial Engineering Management Scienc, 2145 Sheridan Road RM D239, Evanston, IL, 60208, United States Marathons are growing in popularity, requiring significant resources to ensure safety and success. A team from Northwestern University and the Bank of America Chicago Marathon developed a data visualization system that uses analytics to monitor participants and manage resources. The system has been deployed at marathons in Chicago and Houston. n MA51 North Bldg 231B Contemporary Scheduling Emerging Topic: Project Management and Scheduling, in Memory of Joe Leung, Emerging Topic Session Chair: Emrah Cimren, Starbucks, Seattle, WA, 98029, United States 1 - Efficient Approaches for Data-driven Appointment Scheduling Tugce Gurek, University of California-Berkeley, Etcheverry Hall, Berkeley, CA, 94702, United States, Philip Kaminsky We consider a stochastic appointment scheduling problem minimizing the expected deviation from the schedule. We develop a sequencing heuristic that directly uses historical data about task duration rather than making distributional assumptions, and analyze worst-case performance of this heuristic. Given this sequence, we develop an algorithm to set the start time of each task. 2 - Efficient Optimization of Energy Costs Marc E. Posner, Ohio State University, 296 Baker Systems Engineering, 1971 Neil Avenue, Columbus, OH, 43210-1271, United States, Nicholas G. Hall While scheduling of computer or manufacturing systems can effectively improve energy efficiency, minimizing total energy cost is more difficult under time-of-use tariffs. We study a production problem with discretely variable speeds, where energy usage increases with speed. We describe a strongly polynomial algorithm when tasks arrive at known times within the planning horizon. We also show that a polynomial time algorithm is unlikely to exist for many generalizations of our problem. 3 - A Framework for Fashion Retail Planning Emrah Cimren, Starbucks, 2401 Utah Ave South, Seattle, WA, 98134, United States Fashion retailers offer variety of new products and styles at the start of every season and force to clear out stores for the new merchandise by end of the season. Retail planning is a challenging process since every product comes in different styles, colors, and sizes which increase number of stock keeping units exponentially. This talk presents an optimization framework for fashion retail planning. Main objective is to offer right quantity of the right merchandise in the right place at the right time to meet financial goals. n MA50 North Bldg 231A

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