News Archive

November 22nd, 2016

ISE Welcomes Christian Wernz on 11/30/16

Multiscale Decision Theory and its Applications to Healthcare and Beyond

 Seminar by Christian Wernz, Assistant Professor

Department of Industrial and Systems Engineering at Virginia Tech

Wednesday, November 30th  from 4:00 – 5:00 pm

395 Watts Hall, 2041 College Rd N

Complex socio-technical systems, such as healthcare or energy systems, consist of many interdependent decision makers with different, often conflicting, interests, who interact with each other across multiple system levels and time scales. To model and analyze the decision-making and system design challenges in such environments, I have developed multiscale decision theory (MSDT). MSDT is a modeling approach that combines game theory, Markov decision processes and dependency graphs. In this talk, I will present the foundations of MSDT and how I have applied this methodology to study incentives and payment innovations in the U.S. healthcare system. Specifically, I have analyzed the Medicare Shared Savings Program (MSSP) for Accountable Care Organizations (ACOs) and its effect on medical technology investments and use. The analysis provides insights for policy makers on how to improve MSSP. Results also inform ACOs, hospitals and physicians on how to optimally respond to this new incentive mechanism. Beyond healthcare, I will discuss applications of MSDT to systems engineering and energy systems.

Dr. Christian Wernz is an Assistant Professor in the Department of Industrial and Systems Engineering at Virginia Tech, where he is the Director of the Multiscale Decision Making (MSDM) laboratory. He received his doctorate in Industrial Engineering and Operations Research from the University of Massachusetts Amherst in 2008. He obtained his bachelor’s and master’s degree in Business Engineering from the Karlsruhe Institute of Technology (KIT), Germany, in 1999 and 2003, respectively. In his research, Dr. Wernz models and analyzes decision-making challenges in organizations and complex systems. His methodological expertise lies in multiscale decision theory, game theory, Markov decision processes, decision analysis and simulation. He has applied these and other operations research methods to study problems in various socio-technical systems with a focus on healthcare. His research has been funded by the National Science Foundation (NSF), the Agency for Healthcare Research & Quality (AHRQ), the Harvey L. Neiman Health Policy Institute, Rolls-Royce, Dell and other industry partners.

November 18th, 2016

Recent ISE Faculty Grant Awards

In the fall of 2016, ISE faculty were awarded a 5-year Training Project Grant from the National Institute for Occupational Safety and Health (NIOSH), the United States federal agency responsible for conducting research and making recommendations for the prevention of work-related injury and illness.  Through the grant, they can provide support to graduate students who wish to obtain a master’s degree in industrial engineering, while pursuing their interests in occupational safety and ergonomics. Faculty on the project are Carolyn Sommerich, Steve Lavender, Bill Marras, Mike Rayo, Phil Smith and Dave Woods. You can read more about this master’s level graduate program here.

Another grant was awarded to ISE faculty and researchers in the fall of 2016 from Midmark to assess effects of exam room equipment and layout on workflow and perceptions of patients and clinical staff. Researchers involved include Carolyn Sommerich (ISE), Steve Lavender (ISE), Liz Sanders (Design), and Kevin Evans (SHRS).

Additionally, a 2-year grant was awarded in summer of 2016 from the Ohio BWC Research Grant Program to investigate current methods employed by firefighter-paramedics (FFP) for handling heavier patients and develop improved methods that could reduce the risk of injury to FFP posed by current methods. Researchers on the project are Steve Lavender, Carolyn Sommerich and Bill Marras.

November 17th, 2016

ISE Students Attend SHPE Conference

ISE students, Alejandro Nunez and Manuara Costa, recently returned after attending the Society of Hispanic Professional Engineers (SHPE) national conference on November 2-6, the nation’s largest annual Hispanic STEM conference. The conference is an opportunity for engineering companies to recruit talented students from SHPE membership. Both students who attended were sponsored by the ISE department and are on the E-board of SHPE’s OSU chapter.

Alejandro and Manuara were interested in attending the event to network with companies and other student chapters and obtain a Co-Op/Internship. Alejandro was able to obtain a Co-Op with Delta Airlines through the conference this year and Manuara has attended the conferences since she was a freshman and all of her internships have come from it.

The SHPE mission is to change lives by empowering the Hispanic community to realize its fullest potential and to impact the world through STEM awareness, access, support and development.

You can see photos of the event on the SHPE Facebook page here.

November 15th, 2016

ISE Welcomes Ekundayo Shittu on 11/22/16

Investments in Energy Systems under Uncertainties in Climate Change Policies and Technological Learning

Seminar by Ekundayo Shittu, Assistant Professor

Engineering Management & Systems Engineering, The George Washington University

Tuesday, November 22 from 4:00 – 5:00 pm

210E Baker Systems, 1971 Neil Avenue

When viewed with the lens of developing solution strategies, global climate change is a classic problem of decision making under uncertainty. This presentation highlights the management of responses to climate change specifically as it relates to energy technology investment decisions under two streams of uncertainties. First, we explore the investments of a profit-maximizing firm into a portfolio of energy systems in response to uncertainty in a climate change regulatory policy. We pay close attention to the representation of technological change to investigate how a firm’s optimal investment is influenced by the presence of a set of different technologies, and uncertainty in a carbon tax. We find that the key drivers of the optimal energy technology set are the elasticities of substitution between the different energy sources, and the relative efficacy of research and development (R&D) into energy sources. Second, we extend this analysis by unpacking the role of learning in managing the capacity expansion of existing and emerging energy technologies. Specifically, we address how stochastic learning rates impact capacity investments into a range of electricity generating technologies. Understanding the managerial or strategic response to uncertainty in energy technological learning is particularly important as decision makers face competing energy technology R&D portfolios, dwindling and unstable financial resources, and an imminent climate change policy. With the aid of cost-constrained risk-minimizing inter-temporal optimization model of a reference global energy system, we investigate the effects of uncertainties in technological learning on electricity capacity additions. We find that (1) the willingness to hedge against the inherent risks associated with uncertainty in energy technological learning is positively correlated with the risk premium; (2) near-term or early investments are required in a mix of sustainable energy technological portfolios as a hedge against learning risk. Using data on 1526 energy companies, investor-owned utilities, and government-owned utilities from 1999 to 2010, we combine these two analysis to propose that the effect of external drivers – competitive learning and regulatory policy – on firms’ new technology investments depends on a firm’s existing resource stock. While competing firms’ new technology investments have a stronger effect on incumbents less endowed in the existing technology, regulatory policy pushes incumbents heavily endowed in the existing technology toward environmentally sustainable investments.

This presentation concludes with a peek into future research streams particularly on (1) an innovative agent-based modeling (ABM) framework to evaluate the interconnections among food, energy and water systems, (2) dynamic computable general equilibrium modeling to harness effective insurance decision making strategies in response to natural and climate change induced disasters, and (3) vaccine supply chain logistics in least developed countries.

Keywords: Carbon tax, Energy system; Investments; Learning; Profit-maximization; R&D; Risk; Technological change; Uncertainty.

Professor Ekundayo Shittu conducts basic and applied research that take a systems engineering approach to aid decision making under uncertainty on investments into energy technology portfolios and the economics of climate change response policies. Pivotal to his research is the examination of how key stakeholders deal with climate change risk and uncertainty. He examines ways of integrating formal decision tools and microeconomics to develop climate policies that aid the adoption of emerging energy systems. Current projects include understanding the effects of uncertainty in technological learning on energy capacity additions, investigating how energy firms’ investments are shaped by competitive and regulatory pressures, studying how to adequately value emerging energy systems given the evolution of storage technologies to mitigate intermittency, investigating effective resource use strategies at the nexus of food, water and energy systems, and studying the platforms for an effective and efficient disaster response system. He was a Lead Author on Chapter 2, “Integrated Assessment of Risk and Uncertainty of Climate Change Response Policies,” fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). He is a reviewer for IEEE Transactions on Engineering Management, European Journal of Operations Research, Production and Operations Management journal, Systems Engineering, Energies, Energy Engineering, Vaccines, etc. He holds a doctorate degree in Industrial Engineering and Operations Research from the University of Massachusetts Amherst, a masters degree in Industrial Engineering from the American University of Cairo, and a Bachelors in Electrical Engineering from the University of Ilorin.

November 7th, 2016

ISE Welcomes Ahmed Saif on 11/18/16

Cold Supply Chain Design with Environmental Considerations: A Simulation-Optimization Approach

Seminar by Ahmed Saif, Postdoc

HEC Montréal

Friday, November 18th, 11:30 am – 12:30 pm

210E Baker Systems, 1971 Neil Avenue

In response to strict regulations and increased environmental awareness, firms are striving to reduce the global warming impact of their operations. Cold supply chains have high levels of greenhouse gas emissions due to the high energy consumption and refrigerant gas leakages. We model the cold supply chain design problem as a mixed-integer concave minimization problem with dual objectives of minimizing the total cost and the global warming impact. Demand is modeled as a general distribution, whereas inventory is managed using a known policy but without explicit formulas for the inventory cost and maximum level functions. We propose a novel hybrid simulation-optimization approach to solve the problem. Lagrangian decomposition is used to compose the model into an integer programming subproblem and sets of single variable concave minimization subproblems that are solved using simulation-optimization. We provide closed-form expressions for the Lagrangian multipliers so that the Lagrangian bound is obtained in a single iteration, alongside a feasible solution. The approach is verified through testing on two realistic cases from different industries, and managerial insights are drawn.

Ahmed Saif is a postdoctoral fellow in the department of Decision Sciences at HEC Montreal. He completed his Ph.D. in Management Sciences from the University of Waterloo in January 2016. He also holds a master’s degree in Engineering Systems & Management and an MBA. Ahmed’s research interests lie in the area of optimization under uncertainty and data analytics. His current research focuses on data-driven robust optimization approaches and their applications in supply chains, particularly integrated, multistage supply chain network design problems. He worked also on warehouse logistics and developed performance improvement approaches that combine data analytics and optimization tools and that utilize the sheer amount of order processing data collected by warehouses. Furthermore, he conducted research in global optimization, healthcare logistics, airline crew scheduling and hybrid power systems. Ahmed has a diverse teaching experience in North American and International postsecondary institutions. Moreover, he worked in engineering and business consulting for about 4 years and had multiple industry internships while pursuing graduate degrees. Ahmed’s research attracted funding from federal and provincial agencies and from the industry.

November 7th, 2016

ISE Welcomes Shuzhong Zhang on 11/16/16

New first-order algorithms for solving block-structured optimization models

Seminar by Shuzhong Zhang

Professor and Head

Department of Industrial and Systems Engineering, University of Minnesota

Wednesday, November 16th, 4:00 – 5:00 pm

395 Watts Hall, 2041 College Rd. N.

In the context of Big Data analytics, first-order algorithms (referring to the solution procedures where no more than gradient information is required in the process) for large-scale structured optimization models have been popular among researchers in the fields including Operations Research and Machine Learning. One important type of first-order algorithms is called the Alternating Direction Method of Multipliers (ADMM). In the past few years, an intensive stream of research effort has been paid to the performance of the ADMM and its many variants designed to accommodate various formulations arising from applications. In this talk, we shall survey several aspects of the afore-mentioned research effort, and present some new results including the convergence of a randomized multi-block ADMM.

Shuzhong Zhang is Professor and founding head of Department of Industrial and System Engineering, University of Minnesota. He received a B.Sc. degree in Applied Mathematics from Fudan University in 1984, and a Ph.D degree in Operations Research from Erasmus University in 1991. He had held faculty positions at Department of Econometrics, University of Groningen (1991-1993), and Econometric Institute, Erasmus University (1993-1999), and Department of Systems Engineering & Engineering Management, The Chinese University of Hong Kong (1999-2010). He received the Erasmus University Research Prize in 1999, the CUHK Vice-Chancellor Exemplary Teaching Award in 2001, the SIAM Outstanding Paper Prize in 2003, the IEEE Signal Processing Society Best Paper Award in 2010, and the 2015 SPS Signal Processing Magazine Best Paper Award. Dr. Zhang was an elected Council Member at Large of the MPS (Mathematical Programming Society) (2006-2009), and served as Vice-President of the Operations Research Society of China (ORSC) (2008-2012). He serves on the Editorial Board of several academic journals, including Operations Research, and Management Science.

November 1st, 2016

Ohio State INFORMS Student Chapter Wins Annual Award

The Ohio State University INFORMS Chapter has been selected as a winner of the INFORMS 2016 Student Chapter Annual Award at Magna Cum Laude level. This is a level higher than the group won last year. The Student Chapter Annual Awards recognize their achievements in the past year and serve as a motivation for them to perform well. The award will be presented to them at the Student Awards Ceremony at the upcoming INFORMS Annual Meeting in Nashville, Tennessee on November 14th, 2016.

October 27th, 2016

Student Group, Big Data and Analytics Association (BDAA), Receives Outstanding Innovation and Change Award

The student group Big Data and Analytics Association (BDAA) recently received the Ohio Union’s “Outstanding Innovation and Change Award”. The award recognizes student groups that have made noteworthy progress toward previously articulated goals. In just 3 years, they have increased their active members ten-fold as students and OSU have made efforts to increase analytics on campus.

ISE undergraduates with a special interest in data analytics can pursue the “data analytics and data-driven optimization” track or the “supply chain management and logistics” track. You can read about curriculum requirements on the ISE website. Graduate students can similarly complete M.S. concentrations in these same areas.

You can read more about BDAA’s efforts and recent growth at https://engineering.osu.edu/news/2016/10/ambitious-student-organization-has-big-ideas-big-data

You can learn more about BDAA at http://bdaaatohiostate.org/.

October 24th, 2016

ISE Welcomes Aaron Bloom on Nov. 2

Section Manager, Energy Forecasting and Modeling Group

A seminar by Aaron Bloom

Project Manager/Engineer – Electricity Section Supervisor, National Renewable Energy Laboratory

Wednesday, November 2, 2016; 4:00 – 5:00 pm

395 Watts Hall, 2041 College Rd. N.

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the Eastern Interconnection. In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and solar, we developed state of the art tools, data and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL’s high-performance computing capabilities and new methodologies to model operations, we found that the Eastern Interconnection, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and solar PV at a 5-minute level under a variety of conditions. Our simulations achieve instantaneous penetrations that exceed 50% of load while meeting an annual penetration of 30% on an energy basis.  In this work, we analyze potentially challenging system conditions that occur in the simulations and identify opportunities for innovation, regulatory reform, and changes in operating practices that require further analysis to enable the transition to a system with more wind and solar PV. We also released our model and a variety of visualization tools to the public.

Aaron Bloom graduated from the John Glenn College in 2005. After earning his Master’s in Public Administration he moved to Washington, DC to work at the Federal Energy Regulatory Commission where he worked on various rulemakings, market design issues, and NERC standards. In 2012 he joined the National Renewable Energy Laboratory in Golden, CO. There he leads an interdisciplinary team of power systems analysts that study the impact of clean energy technologies on power systems using a range of models and tools. His research is focused on power system planning and electricity market design. He very much enjoys his job and loves riding mountain bikes in Colorado with his family.

October 20th, 2016

Tenure Track Faculty Position at ISE: Complex Large Scale Systems Modeling & Non-Linear Optimization

The Department of Integrated Systems (ISE) at The Ohio State University, one of the nation’s top ten public universities, invites applications for a tenure-track position focusing on Complex Large Scale Systems Modeling and Non-Linear Optimization. All faculty ranks will be considered. ISE offers degrees (BS, MS and Ph.D.) in Industrial and Systems Engineering. Its undergraduate and graduate programs are consistently among the top programs ranked by USNWR, as the Department has exceptional strength in all major areas associated with the discipline. The Department also has an excellent track record for industry engagement and technology transfer.

This position is partially funded by Ohio State’s Discovery Themes Initiative, a significant faculty hiring investment in key thematic areas in which the university can build on its culture of academic collaboration to make a global impact. The successful candidate will be engaged in the Sustainable and Resilient Economy program (https://discovery.osu.edu/SRE), working with a highly collaborative interdisciplinary community of scholars that is taking a holistic approach to understand how production and consumption systems are linked to ecological systems, and how society can achieve more sustainable and resilient development. In particular, integrated assessment modeling and advanced optimization methods are needed to assess economic, environmental and social impacts, benefits, and trade-offs across different spatial and temporal scales.

The successful applicant will be expected to excel at creating and participating in interdisciplinary research teams. This person will establish a strong research program, attract research funding from federal, state and industry resources, supervise graduate student research, and disseminate the results of such research through high quality peer-reviewed publications. Additionally, this faculty member will extend current course offerings in non-linear optimization and the modeling of complex systems at both the undergraduate and graduate levels. A Ph.D. in operations research or mathematical optimization is highly desired.

Interested candidates should electronically submit a complete curriculum vitae, a separate statement of current and future research interests, a statement of teaching philosophy, contact information for five references and three sample publications to the following email address: freitas.6@osu.edu. The search committee will start reviewing applications for this position on Oct. 1, 2016, but it will remain open until filled.

The Ohio State University is committed to establishing a culturally and intellectually diverse environment, encouraging all members of our learning community to reach their full potential. We are responsive to dual-career families and strongly promote work-life balance to support our community members through a suite of institutionalized policies. We are an NSF Advanced Institution and a member of the Ohio/Western Pennsylvania/West Virginia Higher Education Recruitment Consortium.

The Ohio State University is an Equal Opportunity/Affirmative Action Employer. Applications from women and other underrepresented or minority groups are encouraged. Columbus is a thriving metropolitan community, and the University is responsive to the needs of dual career couples.