Dr. Deanna M. Kennedy, a visiting assistant professor in the Department of Industrial and Systems Engineering at Texas A&M University, will give a talk Monday (Nov. 9) at 3 p.m. in Room 203 of the Zachry Engineering Center.

Kennedy’s talk, “Toward Optimal Team Processes: How Interventions Can Create Process Gains,” is part of the Department of Industrial and Systems Engineering’s seminar series, sponsored by Parsons.

Abstract
The increasing implementation of teams in organizations has motivated research regarding team processes and performance. This study focuses on how mental model convergence, a cognitive process, unfolds to impact team performance. Based on the interplay between cognitive and communicative processes, team communication patterns evoking the underlying mental model convergence process of baseline, intervention, and optimal teams are examined. The baseline team data, collected in a laboratory setting, inform a simulation model of communication from which intervention team data are generated. The performance of these intervention teams is assessed on a neural network performance model. Teams with optimal communication patterns are discovered using genetic algorithm procedures for combinatorial problems with multiple objectives. Results indicate that by shifting the timing of communication patterns using interventions, the mental model convergence process emulates those of optimal teams and process gains are created.

Biography
Dr. Deanna M. Kennedy is a visiting assistant professor in the Department of Industrial and Systems Engineering at Texas A&M University. She received her Ph.D. in management science at the University of Massachusetts-Amherst. She holds an M.B.A. from Golden Gate University at San Francisco and a bachelor’s degree in biological sciences from the University of California, Davis. In 2007, she received the Isenberg Award from U-Mass for academic merit and commitment to the integration of science, engineering and management.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Alan T. Murray, professor with the GeoDa Center for Geospatial Analysis and Computation in the School of Geographical Sciences and Urban Planning at Arizona State University, will give a talk Monday (Nov. 2) at 3 p.m. in Room 203 of the Zachry Engineering Center at Texas A&M University.

Murray’s talk, “Geographic Information System (GIS) Relevance in Optimization,” is part of the Department of Industrial and Systems Engineering’s seminar series sponsored by Parsons Corp.

Abstract
Geographic information systems (GIS) have matured and proven to be an enabling technology, one that is important to many disciplines. This paper provides an overview and discussion of GIS within the context of optimization. The paper highlights how GIS has contributed to spatial optimization approaches in terms of data input, visualization, problem solution and theoretical advances. The significance of GIS in this context is that it is far than a mere spatial data input mechanism, which is a commonly held misconception within industrial engineering and other allied disciplines. A number of spatial optimization models are detailed, identifying past shortcomings and important features now possible through integration with GIS.

Biography
Dr. Alan Murray is a professor in the School of Geographical Sciences and Urban Planning and a researcher in the GeoDa Center for GeoSpatial Analysis and Computation at Arizona State University. He is currently an editor of International Regional Science Review. He obtained a B.S. in mathematical sciences (emphasis in operations research), an M.A. in statistics and applied probability (emphasis in operations research) and a Ph.D. in geography, all from the University of California, Santa Barbara.

His research and teaching interests are in optimization; geographic information science; urban/regional planning and development; and, transportation. A particular emphasis across these interests are location modeling and analysis. He teaches a range of courses in the GISciences, including GIS and business site selection, location analysis and GIS. His research focuses on technical and application oriented topics emergency service planning, crime, sustainability, transit, natural resource management, and infrastructure vulnerability. He is the author of two recent books, Critical Infrastructure: Reliability and Vulnerability (Berlin: Springer) and Business Site Section, Location Analysis and GIS (New York: Wiley), and more than 140 research articles, book chapters and proceedings papers.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Pitu Mirchandani, professor in the School of Computation, Informatics and Decision Systems Engineering at Arizona State University, will give a talk Monday (Oct. 26) at 3 p.m. in Room 203 of the Zachry Engineering Center at Texas A&M University.

Michandani’s talk, “OR-IE-SE Models in Transportation and Traffic,” is part of the Department of Industrial and Systems Engineering’s seminar series sponsored by Parsons Corp.

Abstract
Real-time transportation systems include systems such as real-time traffic signal control systems, real-time transport scheduling systems and real-time freight dispatch systems. Given the vast amount of streaming data that is available through sensors for operating such systems, one can make better real-time decisions if such data is used appropriately. “Real-time” necessarily implies that it is some sort of feedback control, where new decisions are implemented based on “feedback” from sensors that measure the “state of the system.” As such, the attributes of the algorithms embedded in the feedback influence how well the system responds to scheduled and unscheduled external events.

This talk will first present a framework for the design of a real-time adaptive systems and some current work in traffic adaptive signal control systems require that various traffic data be collected in order to develop a traffic model within which the desired performance optimization can be completed. Some OR, systems engineering and statistical models used in a system developed by the presenter, referred to as RHODES, will be discussed. In particular, the next generation of traffic control systems which will have more vehicle location information, will be introduced.

In the second part of the talk, some new applications of the framework for the design of a wide-area adaptive emergency management for evacuations will be briefly discussed using, more appropriately, feedback instead of the predominant open-loop approaches that appear in the literature. In this case the algorithms embedded in the feedback are based on adaptive control of dynamic traffic flows in a network. Unlike in conventional network flow algorithms, traffic flows must now consider vehicular traffic flow theories, as well as random route choices of evacuees. The role of communications, computers and sensors will be discussed in the design of traffic management systems, as well as the role of simulation in the evaluation of such systems.

Bio
Dr. Pitu Mirchandani is a professor in the School of Computation, Informatics, and Decision Systems Engineering at Arizona State University. He also heads the ATLAS (Advanced Transportation and Logistics: Algorithms and Systems) Laboratory at ASU. Mirchandani earned a bachelor’s degree in engineering from the University of California, Los Angeles, and an Sc.D. in operations research from the Massachusetts Institute of Technology.

Mirchandani has several areas of expertise and interests, including theories, models and algorithms in (1) networks, logistics, location and scheduling, (2) transportation engineering, and (3) real-time information and control systems. He has co-authored three books and authored or co-authored more than 100 articles in a variety of journals, magazines and books. He has been on the editorial boards of several major journals. He is a senior member of IEEE, a member of INFORMS, IIE, TRB, and a charter member of ITS-Arizona.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Alexandra Newman, an associate professor in the Division of Economics and Business of the Colorado School of Mines, will give a talk Monday (Oct. 19) at 3 p.m. in Room 203 of the Zachry Engineering Center at Texas A&M University.

Newman’s talk, “A Medley of Operations Research Mining Applications,” is hosted by the Texas A&M Department of Industrial and Systems Engineering and is sponsored by Parsons Corp.

Abstract
In this talk, we present three different applications of operations research in mining: (i) open pit production scheduling, which entails choosing when to mine notional three-dimensional blocks of ore subject to geospatial and operational constraints; (ii) timing the transition between open pit and underground mining, which consists of determining when, if ever, to sink shafts from an open pit mine and switch from surface to underground mining methods; and (iii) underground production scheduling, which is similar in concept to open pit scheduling, but entails details absent in open pit operations. All models are complex integer programs; we show how we exploit problem structure to arrive at more tractable models, and we present numerical results from real mines.

Biography
Alexandra Newman is an associate professor in the Division of Economics and Business at the Colorado School of Mines. She received her Bachelor of Science degree in applied mathematics from the University of Chicago and her Ph.D. in industrial engineering and operations research from the University of California, Berkeley. Prior to her appointment at the School of Mines, she was a research assistant professor in the Operations Research Department at the Naval Postgraduate School. Her research focuses on optimization applications, particularly in logistics, mining and the military.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Stephen W. Searcy, professor and associate head of the Department of Biological and Agricultural Engineering at Texas A&M University, will lecture on biofuels Monday (Oct. 5) from 3 to 3:50 p.m. in Room 203 of the Zachry Engineering Center on campus.

Searcy’s talk, “Logistics Systems for a Nascent Biofuels Industry: Challenges and Opportunities,” is part of the Department of Industrial and Systems Engineering’s seminar series sponsored by Parsons Corp.

Abstract
Government policy and raising crude oil prices are encouraging the development of renewable fuels created from biomass crops. The established goal of 36 billion gallons of liquid fuels in the nation’s energy supply by 2022 means nearly one half billion tons of plant dry matter will have to be collected, stored and transported from remote, distributed fields to central processing facilities.

The challenges associated with the development of a biomass feedstocks logistics system are many. The feedstock has undesirable characteristics (high moisture content, low density), is available only portions of the year, may be constrained by transportation infrastructure, and must compete with profit alternatives. In other words, it is a great engineering problem! We will discuss these challenges and the opportunities they present.

Biography
Stephen Searcy is professor and associate head of the Department of Biological and Agricultural Engineering at Texas A&M University. His area of expertise is development and application of mechatronic systems for agriculture, with emphasis on harvest and transport logistics systems for cotton and energy biomass. He is a registered Professional Engineer, a Fellow of the American Society of Agricultural and Biological Engineers (ASABE), and an active member of ASABE, the National Society of Professional Engineers and the Council of Agricultural Science and Technology.

He holds bachelor’s degrees in agricultural mechanization and agricultural engineering and an M.S. in agricultural mechanization, both from the University of Missouri, and a Ph.D. in agricultural engineering from Oklahoma State University.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Natarajan Gautam

Associate Professor Natarajan Gautam and Assistant Professor Lewis Ntaimo, faculty members in the Department of Industrial and Systems Engineering, have been awarded a two-year, $240,000 grant by the National Science Foundation (NSF) Service Enterprise Systems program for their project “EAGER: Reducing Energy Consumption in Data Centers.”

This grant provides funding to develop models and methodologies for reducing energy consumption in data centers to the maximum extent possible without degrading the quality of service.

Dr. Lewis Ntaimo

The two researchers will integrate stochastic optimization and stochastic optimal control algorithms to determine: a) the optimal set of meta-applications for virtualization in multiple servers; b) the optimal strategy to control server speeds by dynamic voltage scaling; c) optimal rules for real time cluster sizing.

The algorithms will be developed and integrated under a unified multitime scale platform to exploit their benefits. These methodologies will be used to combine pro-active planning with real time control to reduce energy consumption, operating costs and greenhouse gas emissions from data centers.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Natarajan Gautam, associate professor in the Department of Industrial and Systems Engineering at Texas A&M University, will give a talk Monday (Sept 28) at 3 p.m. in Room 203 of the Zachry Engineering Center on campus.

Dr. Natarajan Gautam

Gautam’s lecture, “Optimizing Energy Consumption in Data Centers,” is part of the department’s seminar series sponsored by Parson’s Corp.

Abstract
Energy consumption in industries around the globe can be significantly reduced by controlling operations in existing systems. We begin by broadly describing the scope for energy savings across several industries including data centers, commercial buildings, food packaging, hospitality, etc. Then we describe in detail the problem of controlling resources in data centers that are notorious for inefficiently consuming a phenomenal amount of energy. Data centers typically consist of hundreds to thousands of servers that are not always doing useful work. To conserve energy in data centers, we formulate a dynamic resource management problem that optimally powers servers on or off (cluster sizing), moves applications (using virtualization), and controls server speeds (by dynamic voltage scaling). The key element here is to strike a balance between energy conservation, quality of service, and reliability in a cost-effective manner. We will describe several approaches to solve the resource management problem but focus on a semi-Markov decision process model for a large portion of the seminar.

Biography
Dr. Natarajan Gautam is an associate professor in the Department of Industrial and Systems Engineering with a courtesy appointment in the Department of Electrical and Computer Engineering. Prior to joining Texas A&M in 2005, he was on the industrial engineering faculty at Penn State University for eight years. He received his Ph.D. and M.S. in operations research from the University of North Carolina at Chapel Hill and his B.Tech. in mechanical engineering from Indian Institute of Technology (Madras) in 1993.

Gautam’s interests are in optimal design, control and performance evaluation of stochastic systems, with a recent emphasis on energy and biology. He directs the Group for Research on Engineering ENergy-efficiency (GREEN). The seminar is based on joint work with former students and Assistant Professor Lewis Ntaimo with whom he is working on an NSF grant on the topic.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Dr. Lewis Ntaimo

Dr. Lewis Ntaimo, assistant professor in the Department of Industrial and Systems Engineering at Texas A&M University, and research collaborators at Georgia State University, University of Oklahoma and Oak Ridge National Laboratory have been awarded a $1,000,000 four-year grant by the National Science Foundation’s Cyber-enabled Discovery and Innovation (CDI) program for their project “Collaborative Research: CDI-Type II — Integrated Weather and Wildfire Simulation and Optimization for Wildfire Management.”

Wildfires cause great destruction including the loss of life and damage to property, infrastructure and the environment. The complexity of wildfire management arises from the uncertain dynamic interactions and dependencies among multiple system components. These include highly dynamic and nonlinear wildfire behaviors, weather conditions, and firefighting resource management.

In previous research, these components have been largely treated in isolation in their own fields. To achieve effective wildfire management, decision-making support tools that integrate all these components as a whole are needed. The objective of this project is to develop new models and computation methods that integrate weather prediction, wildfire simulation, data assimilation and stochastic optimization for effective wildfire response management.

The project makes two key paradigm-shifting advances in wildfire modeling and management: 1) coupled weather and wildfire modeling and data assimilation for two-way interactive dynamic weather-wildfire prediction, and 2) Integrated wildfire simulation and stochastic optimization for wildfire containment. The project focuses on computational thinking for understanding the complexity in the natural systems of weather and wildfire behavior, and in the man-made system of firefighting resources management.

Due to the stochastic and multiscale nature of the problem data associated with these systems, the project also involves data assimilation and parallel/distributed computational methods for robust weather and wildfire behavior predictions.

Collaborating with Ntaimo on this project are Dr. Xiaolin Hu from Georgia State University (lead), Dr. Ming Xue and Dr. Yang Hong from the University of Oklahoma, and Dr. James Nutaro of Oak Ridge National Laboratory.

Ntaimo’s portion of the research project will be conducted through the Texas Engineering Experiment Station (TEES) with a funding of $220,000. Ntaimo will collaborate with the Texas Forest Service in College Station to develop new decision models for wildfire emergency response planning.

TEES is the engineering research agency of the State of Texas and a member of The Texas A&M University System.

Popularity: unranked [?]

Dr. Gary M. Gaukler, assistant professor in the Department of Industrial and Systems Engineering at Texas A&M University, will give a lecture on detecting nuclear materials Sept. 21 at 3 pm. in Room 203 of the Zachry Engineering Center on campus.

Dr. Gary M. Gaukler

Gaukler’s talk, “Detecting Nuclear Materials Smuggling: Using Radiography to Improve Container Inspection Policies,” is part of his department’s seminar series and is sponsored by Parsons Corp.

Abstract
This talk provides an overview of some of the current research being performed as part of an ongoing five-year research project on Port and Nuclear Security. In particular, the presentation will focus on a layered container inspection system for detecting illicit nuclear materials using radiography information. We argue that the current inspection system, relying heavily on an intelligence-based Automated Targeting System (ATS) and passive radiation detectors, is inherently incapable of reliably detecting shielded radioactive materials. This motivates the development of a new class of inspection systems that use radiography imaging equipment. These inspection systems are designed to address a fundamental flaw of the ATS-based system, allowing for improved defense against sophisticated adversaries. This talk provides insight into the performance differences of the inspection systems and presents a road map for further systems analysis research on this subject.

Biographical Information
Gary M. Gaukler is an assistant professor in the Department of Industrial and Systems Engineering at Texas A&M University, where he also directs the RFID and Supply Chain Systems Lab. He teaches undergraduate and graduate courses in production and inventory control, logistics, and operations.

His research interests center around systems engineering concepts applied to operations. He is particularly interested in the impact of automatic identification and sensor technologies such as RFID on supply chain and logistics operations. Gaukler is currently the systems analysis team lead for a $7.5 million multidisciplinary research project funded jointly by the National Science Foundation and the U.S. Department of Homeland Security. He has published in academic and business journals on the topics of retail operations, inventory control, supply chain management and manufacturing. He holds a B.Sc. (1998) in engineering and management science from Universitat Karlsruhe, an M.S. (2000) in industrial and systems engineering from Georgia Institute of Technology, an M.S. (2003) in operations research from Stanford University, and a Ph.D. (2005) in management science and engineering from Stanford University.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]

Robert L. Smith, the program director for Operations Research at the National Science Foundation (NSF), will give a talk on optimization Monday (Sept. 14) at 3 p.m. in Room 203 of the Zachry Engineering Center at Texas A&M University.

Smith’s talk, “A Fictitious Play Approach to Complex Systems Optimization,” is part of the Department of Industrial and Systems Engineering’s seminar series, sponsored by Parsons Corp.

Smith is currently on leave from his position as the Altarum/ERIM Russell D. O’Neal Professor of Engineering in the Department of Industrial and Operations Engineering at the University of Michigan.

Abstract
Complex systems consisting of a large number of interacting components are in practice increasingly modeled through computer simulations rather than via traditional equation based approaches. The resulting model typically allows for little or no structural assumptions on the form of the objective function or constraints, thus posing a challenging optimization problem. We explore in this talk a novel optimization paradigm inherited from game theory that animates the components of the system within a non-cooperative game of identical interest. The optimizations take place though individual best replies of the players, thus vastly reducing the dimensionality of the optimization problems solved (the components’ joint interactions are reflected indirectly through their shared objective function). We will illustrate the approach by discussing an application to intelligent transportation systems. Opportunities for NSF funding in Operations Research will be discussed at the end of the talk.

Biography
Robert L. Smith is director of the Operations Research Program at NSF. He received his Ph.D. in engineering science from the University of California, Berkeley. He holds a bachelor’s degree in physics from Harvey Mudd College and an MBA from UC-Berkeley. He is on leave from the University of Michigan in Ann Arbor where he is the Altarum/ERIM Russell D. O’Neal Professor of Engineering as well as director of the Dynamic Systems Optimization Laboratory. He is an associate editor of Operations Research and past associate editor of Management Science, and is the author of nearly 100 peer-reviewed publications. Smith is a Fellow of the Institute for Operations Research and the Management Sciences.

Submitted by Katherine Edwards, kedwards@tamu.edu

Popularity: unranked [?]