Operations Research Department Research Articles

William T. Ziemba and a Brief Look at HisJournal of Portfolio ManagementLegacy

1. John Guerard 1. is the director of quantitative research at McKinley Capital Management, Inc., in Anchorage, AK. (jguerard{at}mckinleycapital.com) 2. John M. Mulvey 1. is a professor in the Department of Operations Research and Financial Engineering at Princeton University in

The Pransky interview: Dr Ken Goldberg, Professor, Industrial Engineering and Operations Research, UC Berkeley; Inventor and Artist

Purpose The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business, and personal experience of a prominent, robotic industry PhD and inventor regarding his pioneering efforts and the commercialization of bringing a technological invention to market. The paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Ken Goldberg, an inventor working at the intersection of art, robotics, and social media. He joined the UC Berkeley faculty in 1995 where he is the UC Berkeley William S. Floyd Jr Distinguished Chair in Engineering and recently served as Chair of the Industrial Engineering and Operations Research Department. He has secondary appointments in UC Berkeley’s Electrical Engineering/Computer Science, Art Practice and the School of Information. Goldberg also holds an appointment at the UC San Francisco Medical School’s Department of Radiation Oncology where he pursues research in medical robotics. Goldberg is Director of the CITRIS “People and Robots” Initiative and the UC Berkeley’s Laboratory for Automation Science and Engineering (AUTOLAB) where he and his students research machine learning for robotics and automation in warehouses, homes, and operating rooms. In this interview, Goldberg shares some of his personal and business perspectives from his career-long pursuit of making robots less clumsy. Findings Goldberg earned dual BS degrees in Electrical Engineering and Economics from the University of Pennsylvania in 1984, and MS and PhD degrees in Computer Science from Carnegie Mellon University in 1990. Goldberg also studied at Edinburgh University and the Technion. From 1991-95 he taught at the University of Southern California, and in fall 2000, he was visiting faculty at the MIT Media Lab. Goldberg and his students pursue research in three primary areas: Geometric Algorithms for Automation, Cloud Robotics, and Robot Learning. Originality/value Goldberg developed the first complete algorithms for part feeding and part fixturing, and developed the first robot on the Internet. His inventions have been awarded nine US Patents. Goldberg has published over 250 peer-reviewed technical papers and edited four books. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (T-ASE). He is also Co-Founder of the Berkeley AI Research (BAIR) Lab, the Berkeley Center for New Media (BCNM), the African Robotics Network (AFRON), the Center for Automation and Learning for Medical Robotics (CAL-MR), the CITRIS Data and Democracy Initiative (DDI), Hybrid Wisdom Labs, and Moxie Institute. He has presented over four hundred keynote and invited lectures. Goldberg's artwork, closely linked with his research, has appeared in over seventy venues. Ken was awarded the Presidential Faculty Fellowship in 1995 by Bill Clinton, the Joseph Engelberger Robotics Award in 2000, elected IEEE Fellow in 2005, and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016.

MGIS 및 유전자 알고리즘을 활용한 정보자산 최적배치에 관한 연구

Department of Operations Research, Korea National Defense UniversityThe literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.

A Real-World Network Modeling Project

The Operations Research Department at the Naval Postgraduate School educates experienced junior military officers in state-of-the-art operations research methods. As part of the educational program all officers go through a standard graduate course on network modeling. Within that course, students complete a class-long network modeling project of a real-world infrastructure system that solidifies their understanding of operations research concepts and moves the learning experience beyond the classroom. Through the project, students abstract their real-world problems into mathematics, repeatedly evaluate the connection between the mathematics and reality, and reason about the model results. The project has educational, research, and practical benefits. On occasion, students make discoveries of such significance that we have contacted the infrastructure system operators with briefings on the student analysis results. Some student projects have eventually influenced Department of Homeland Security and Department of Defense policy. We detail what makes the network modeling project work, and how to implement it in other universities.

Theory Applied—Experience Tours at the Naval Postgraduate School

The Operations Research Department at the Naval Postgraduate School (NPS) in Monterey, California educates analysts who are fully capable of conducting independent analytical studies of military problems. Significant to this education is an opportunity to apply theory from the classroom to a problem from the real world. Halfway through the two year program, each student is encouraged to participate in a three to six week experience tour at a Department of Defense (DoD) analytical organization. During this tour students obtain hands-on experience working military operations research problems alongside experienced analysts. They also identify a thesis topic for follow-on research when they return to the NPS. Faculty members supervise the students' thesis research during the remainder of their time in Monterey. The theses are more than just a graduation requirement, some result in publications in refereed journals and most solve pressing problems for the DoD. We recognize that the unique set of circumstances here at NPS makes this all possible but hold strongly to the idea that applied experience is essential to our graduates and that aspects of our program are exportable to civilian universities.

Erratum to: Adverse drug reactions to antiretroviral therapy (ARVs): incidence, type and risk factors in Nigeria

Author details Department of Operations Research, HIV/AIDS Program. Population Council, Nigeria. No. 16, Mafemi Crescent, Utako, Abuja, Nigeria. Department of Health Policy and Management, Diadem Consults Ltd, Abuja, Nigeria. Management Sciences for Health, Abuja, Nigeria. Howard University PACE Center, Washington, USA. Society for Family Health, Abuja, Nigeria. Family Health International 360, Pretoria, South Africa. UNDP Regional Center for Europe and Central Asia, Bratislavia, Slovakia.

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Robust policies for the transformer acquisition and allocation problem

As the electric transmission system in the U.S. ages, mitigating the risk of high-voltage transformer failures becomes an increasingly important issue for transmission owners and operators. This paper addresses this issue by presenting an in-depth study of different policies to manage the acquisition and allocation of high-voltage transformers over time. We analyze PJM’s transmission system by simulating and evaluating different policies under various assumptions and parameter settings. This allows us to characterize different policies and more generally learn about the behavior of the system. Our findings conclude that the approximate dynamic programming-based approach introduced in Enders et al. (Technical report, Department of Operations Research and Financial Engineering, Princeton University, 2008) outperforms the policy that PJM currently uses based on several performance measures. We analyze issues of practical importance to PJM such as the effect of system wide optimization vs. optimization by transmission owner. Our findings suggest that system wide decision making considerably reduces the costs associated with transformer failures and replacements.

My Stanford Days as a Graduate Student with R.E. Kalman [Historical Perspectives

I started my graduate studies at Stanford University during the autumn quarter of 1967, after having obtained the bachelor's degree in electrical engineering from the Georgia Institute of Technology in 1967. For me, the biggest shift in going from undergraduate student to graduate study at Stanford was the level of mathematics. In particular, the system theory course sequence in electrical engineering at Stanford required that students have a strong understanding and working knowledge of linear algebra, which I did not begin to acquire until the spring quarter of 1969 when I took a linear algebra course in the Department of Mathematics. After that course, I was finally able to take System Theory 363A, the first course in Stanford's electrical engineering system theory sequence at that time. I took the course from a remarkable adjunct professor named Rod Edwards who turned me on to mathematical system theory as an area of study. In the next quarter, I took the first course of a two-course sequence in the Department of Operations Research titled Mathematical System Theory 347A and B, which was taught by Prof. R.E. Kalman.

An Interview with David Alderson

David Alderson has become a leading advocate for formulating the foundations of network science so that its predictions can be applied to real networks. He is an assistant professor in the Operations Research Department at the Naval Postgraduate School in Monterey, Calif., where he conducts research with military officer-students on the operation, attack, and defense of network infrastructure systems. Ubiquity interviewed him to find out what is going on.