Alumni Win Awards at Americold

 Umit Sarilar and Sarah Moore, recent IMSE grads, were awarded Experienced Industrial Engineer 2016 and Industrial Engineer Tech 2016.

Both of the students gained experience through their Capstone Class and Senior Design Project.
“It was a great year for UTA graduates in Americold and I wanted to say thank you again for helping me to initiate that senior design project last year.” Umit Sarilar
Congratulations to you both!
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Seminar Series: Guest Speaker Thursday 3/30

Dr.  Caroline Krejci from the Department of Industrial and Manufacturing Systems Engineering at Iowa State University will present a Seminar this Thursday, March 30, at 1:30pm in the Engineering Research Building (ERB) 228.  Dr. Krejci’s presentation title, abstract, and biographical sketch are below.

All students and faculty are encouraged to attend.

Author: Dr. Caroline Krejci
Title: Evaluating Sociotechnical Systems Using Agent-Based Modeling
Location: Engineering Research Building (ERB) 228
Date: Thursday, March 30
Time: 1:30pm – 2:50pm

Abstract: Mathematical modeling is often used to optimize or gain a better understanding of the behavior of sociotechnical systems (e.g., supply chains, production systems).  However, such models typically ignore or make unrealistic assumptions about the behavior of a system’s human participants, which can limit model validity.  By contrast, agent-based modeling (ABM) is a computational modeling method that allows the human actors and/or organizations in sociotechnical systems to be modeled as autonomous and intelligent agents.  These agents can be programmed with empirically valid human characteristics and capabilities, including bounded rationality, social skills, and the ability to adapt and learn from accumulated experience and system feedback.  Over time, individual agent decisions, interactions, and adaptations may yield emergent system-level behaviors of interest, which are observable via ABM outputs.  ABM can also be combined with other modeling methods, such as discrete-event simulation, GIS, and building energy simulators.  These hybrid simulation models enable the integration of a variety of useful nonsocial system properties (e.g., queueing behavior) into an ABM.

This presentation will describe several novel approaches to sociotechnical system modeling using ABM and hybrid simulation.  The attributes, preferences, and decision-making processes of the agents in these models are empirically informed, using data that was collected via interviews, surveys, and experiments.  The resulting models have been used to provide strategic decision support to participants and stakeholders in regional food supply chains, humanitarian relief chains, urban communities, and production systems.

Biographical Sketch: Dr. Caroline Krejci is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at Iowa State University.  She worked as an industrial engineer for UPS and as an operations engineer for Lutron Electronics before earning a Ph.D. in Industrial Engineering from the University of Washington in 2013.  Dr. Krejci’s research interests are focused on the development of quantitative methodologies for the analysis and management of sociotechnical systems.  She specializes in modeling supply networks as complex adaptive systems, which enables the realistic representation of network participants as autonomous and heterogeneous agents that are capable of complex planning, decision making, interactions, and adaptations in a dynamic environment.  Such complex systems often exhibit unpredictable and nonlinear behavior, which can be captured through the use of agent-based modeling techniques.  Dr. Krejci is particularly interested in using these techniques to explore the implications of different management policies on long-term social, environmental, and economic system sustainability.

Krejci_photo

Speaker Series Presentation- Monday 3/27

Dr. Ramtin Madani from the Department of Electrical Engineering from the University of Texas at Arlington will present at the Seminar Monday March 27 at 1:15pm in Nedderman Hall 106.  Dr. Madani’s presentation title, abstract, and biographical sketch are below.

All students and faculty are encouraged to attend. Attendance is expected for GTAs and on-campus GRAs. There will be signature sheets for GTA’s located in the room. Please sign in to note your attendance.

Author: Dr. Ramtin Madani
Title: Mathematical Programming Methods for Control and Optimization of Power Systems
Location: Nedderman Hall Room 106
Time: 1:15pm – 2:15pm

Abstract: This talk is concerned with the development of efficient computational methods for the design, operation and control of power systems. Due to difficulties such as the nonlinearity induced by laws of physics and binary parameters, several power system optimization problems cannot be solved based on a full model and have remained open for decades. Real-world approaches involve inherited approximations and heuristics, based on linearization and local search algorithms, that are believed to be costly and jeopardize the operation of the grid. We introduce a variety of graph-theoretic and penalized optimization techniques that facilitate performing fundamental, yet challenging optimization tasks such as the optimal power flow, state estimation and security constraint unit commitment. A novel method will be discussed for the classical problem of designing distributed controllers for stochastic systems with applications to renewable energy. Lastly, a distributed numerical algorithm with low-complex iterations is presented in order to address the need for solving large-scale conic optimization programs for power system applications. The goal is to develop the essential pieces for a powerful optimization and decision-making engine tailored for the modern grid requirements. The proposed techniques are simulated on real-world nationwide electrical systems.

Biographical Sketch: Ramtin Madani is an Assistant Professor with the Department of Electrical Engineering at the University of Texas at Arlington. He received the Ph.D. degree in electrical engineering from Columbia University in 2015 and was a postdoctoral scholar in the Department of Industrial Engineering and Operations Research at University of California, Berkeley in 2016. His research focuses on developing algorithms for optimization, control and design of real-world complex systems such as electric power grids. Ramtin Madani’s work has received the 2016 Best Publication Award in Energy from the Institute for Operations Research and the Management Sciences (INFORMS) Section on Energy, Natural Resources, and the Environment. His recent work has been a best paper finalist for the flagship conference of the Control Systems Society (53rd Annual Conference on Decision and Control).

Dr.Madani