ISE Seminar Calendar
http://illinois.edu/calendar/list/3605
Industrial and Enterprise Systems Engineering Seminars/SpeakersISE Seminar-Approximation-Friendly Discrepancy Rounding
http://illinois.edu/calendar/detail/3605/32916544
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32916544Thu, 08 Oct 2015 15:00:00 CDT<p><strong>Abstract</strong></p>
<p style="text-align: justify;">We consider the general problem of rounding a fractional vector to an integral vector while (approximately) satisfying a number of linear constraints. Randomized rounding and discrepancy-based rounding are two of the strongest rounding methods known. However these algorithms are very different and the violation bounds achieved by them are incomparable. Randomized rounding leads to good multiplicative violation, whereas discrepancy-based rounding leads to much better additive violation. Our first contribution is a new discrepancy-based rounding algorithm that simultaneously yields strong additive as well as multiplicative violation bounds. Our second contribution is an extension of this rounding algorithm to matroid polytopes.</p>
<p>This is joint work with Nikhil Bansal.</p>
<p><strong>Biography</strong></p>
<p style="text-align: justify;">Viswanath Nagarajan is an Assistant Professor in the Department of Industrial and Operations Engineering, University of Michigan. From 2009-14 he was a Research Staff Member at IBM T.J. Watson Research Center. He has a Ph.D. in Algorithms, Combinatorics and Optimization from Carnegie Mellon University (2009) and a BTech in Computer Science from IIT Bombay (2003). Dr. Nagarajan's research interests are in combinatorial optimization and approximation algorithms, especially as applied to routing, location and scheduling. He received the Gerald L. Thompson dissertation award at CMU (2009), a best paper award at the European Symposium on Algorithms (2010), and two Outstanding Technical Achievement awards at IBM (2012 and 2014).</p>ISE Seminar-Coordinate Descent Methods
http://illinois.edu/calendar/detail/3605/32954821
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32954821Thu, 22 Oct 2015 16:00:00 CDT<p><strong>Abstract</strong></p>
<p style="text-align: justify;">Coordinate descent is an approach for minimizing functions in which just one or a few variables are allowed to change at each iteration, while the others are held fixed. This approach has been popular in applications since the earliest days of optimization, because it is intuitive and because the low-dimensional searches that take place at each iteration are inexpensive in many applications. In recent years, the popularity of coordinate descent methods has grown further because of their usefulness in data analysis. In this talk we describe situations in which coordinate descent methods are useful, and discuss several variants of these methods and their convergence properties. We describe recent analysis of the convergence of asynchronous parallel versions of these methods, which achieve high efficiency on multicore computers.</p>
<p style="text-align: justify;"><strong>Biography</strong></p>
<p style="text-align: justify;">Stephen J. Wright is the Amar and Balinder Sohi Professor of Computer Sciences at the University of Wisconsin-Madison. His research is on computational optimization and its applications to many areas of science and engineering. Prior to joining UW-Madison in 2001, Wright was a Senior Computer Scientist at Argonne National Laboratory (1990-2001), and a Professor of Computer Science at the University of Chicago (2000-2001). He has served as chair of the Mathematical Optimization Society and as a Trustee of the Society for Industrial and Applied Mathematics (SIAM). He is a Fellow of SIAM. In 2014, he won the W.R.G. Baker award from IEEE.<br /><br />Wright is the author or coauthor of widely used text / reference books in optimization including "Primal Dual Interior-Point Methods" (SIAM, 1997) and "Numerical Optimization" (2nd Edition, Springer, 2006, with J. Nocedal). He has published widely on optimization theory, algorithms, software, and applications. <br /><br />Wright is editor-in-chief of the SIAM Journal on Optimization and has served as editor-in-chief or associate editor of Mathematical Programming (Series A), Mathematical Programming (Series B), SIAM Review, and Applied Mathematics and Computation.</p>ISE Seminar-Combinatorial Characterizations in Semidefinite Programming Duality
http://illinois.edu/calendar/detail/3605/32915827
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32915827Thu, 29 Oct 2015 16:00:00 CDT<p style="text-align: justify;"><strong>Abstract</strong></p>
<p style="text-align: justify;">Semidefinite programs (SDPs) generalize linear programs by replacing the nonnegativity constraint by positive semidefiniteness of a variable matrix. SDPs are remarkably broadly applicable in areas as diverse as engineering and combinatorial optimization.</p>
<p style="text-align: justify;">Duality plays a central role in SDP, just like in linear programming. However, in SDP, unlike in LP, pathological phenomena occur: nonattainment of the optimal value; positive duality gaps between the primal and dual problems; and the failure of Farkas’ lemma to prove infeasibility.</p>
<p style="text-align: justify;">We provide combinatorial characterizations for several fundamental problems in SDP. The first is infeasibility: we give an analogy of the row echelon form of a linear system of equations, and show that a semidefinite system is infeasible exactly if by elementary operations we can bring it to a format which is trivially so. The second is the pathological behavior of feasible systems: we give an “excluded minor” type characterization of such systems, and again use elementary operations to bring them to a form, where the pathological behavior is easily recognizable.</p>
<p style="text-align: justify;">Part of this work is joint with Minghui Liu.</p>
<p style="text-align: justify;"><strong>Biography</strong></p>
<p style="text-align: justify;">Gabor Pataki received his MS degree from Eotvos Lorand University in Budapest in 1990, and his PhD in Algorithms, Combinatorics and Optimization from Carnegie Mellon University in 1996. He has been at UNC Chapel Hill since 2000. His research area is in convex analysis, convex optimization, mainly in semidefinite programming.</p>
<p> </p>ISE Seminar-Variational Analysis: What is it?
http://illinois.edu/calendar/detail/3605/33002754
Other Seminarhttp://illinois.edu/calendar/detail/3605/33002754Fri, 06 Nov 2015 15:00:00 CST<p><strong>Abstract</strong></p>
<p style="text-align: justify;">Variational analysis has been recognized as an active and rapidly growing area of applied mathematics and operations research motivated mainly by the study of constrained optimization and equilibrium problems, while also applying perturbation ideas and variational principles to a broad class of problems and situations that may be not of a variational nature. One of the most characteristic features of modern variational analysis is the intrinsic presence of nonsmoothness, which naturally enters not only through the initial data of the problems under consideration but largely via variational principles and perturbation techniques applied to a variety of problems with even smooth data. Nonlinear dynamics and variational systems in applied sciences also give rise to nonsmooth structures and motivate the development of new forms of analysis that rely on generalized differentiation. This talk is devoted to discussing some basic constructions and results of variational analysis and its remarkable applications to optimization and control.</p>
<p style="text-align: justify;"><strong>Biography</strong></p>
<p style="text-align: justify;">Boris Mordukhovich is Distinguished University Professor of Mathematics at Wayne State University. He has around 400 publications including several monographs. Among his best known achievements are the introduction and development of powerful constructions of generalized differentiation and their applications to broad classes of problems in variational analysis, optimization, equilibrium, control, engineering, economics, and other fields. Mordukhovich is a SIAM Fellow, an AMS Fellow, and a recipient of many international awards and honors including multiple Doctor Honoris Causa degrees from academic institutions over the world. He is named a Highly Cited Researcher in Mathematics and Statistics. His research has been supported by continued grants from the National Science Foundation and the Air Force Office of Scientific Research.</p>ISE Seminar
http://illinois.edu/calendar/detail/3605/32915828
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32915828Thu, 03 Dec 2015 16:00:00 CSTISE Seminar
http://illinois.edu/calendar/detail/3605/32949894
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32949894Thu, 31 Mar 2016 16:00:00 CDTIllinois Distinguished Lecure Series in Operations Research-Implementing a New Approach for Managing Supply Chain Risk at the Ford Motor Company
http://illinois.edu/calendar/detail/3605/32916738
Other Seminarhttp://illinois.edu/calendar/detail/3605/32916738Wed, 06 Apr 2016 16:00:00 CDT<p><strong>Abstract</strong></p>
<p style="text-align: justify;">Firms are exposed to a variety of low probability / high impact risks which may disrupt their operations and supply chains. These risks are difficult to predict and quantify, and therefore difficult to manage. As a result, managers may deploy countermeasures sub-optimally, leaving their firms exposed to some risks while wasting resources to mitigate other risks that would not cause significant damage. In a three-year research engagement with Ford Motor Company, we address this practical need by developing a novel risk exposure model that assesses the impact of a disruption originating anywhere in the firm's supply chain. Our approach defers the need to estimate the probability associated with any specific disruption risk until after the company learns how the realization of such a disruption will impair its operations. As a result, the company can make more informed decisions about where to focus its limited risk management resources. We demonstrate how Ford has applied this model to identify previously unrecognized risk exposures and develop mitigation strategies, track changes in risk exposure, and respond to a disruption.</p>
<p><strong>Biography</strong></p>
<p style="text-align: justify;">David Simchi-Levi is a Professor of Engineering Systems at MIT and Chairman of OPS Rules, an operations analytics consulting company. He is considered one of the premier thought leaders in supply chain management and business analytics.</p>
<p style="text-align: justify;">His research focuses on developing and implementing robust and efficient techniques for operations management. He has published widely in professional journals on both practical and theoretical aspects of supply chain and revenue management.</p>
<p style="text-align: justify;">His Ph.D. students have accepted faculty positions in leading academic institutes including U. of California Berkeley, Columbia U., Duke U., Georgia Tech, Harvard U., U. of Illinois Urbana-Champaign, U. of Michigan, Purdue U. and Virginia Tech.</p>
<p style="text-align: justify;">Professor Simchi-Levi co-authored the books M<em>anaging the Supply Chain </em>(McGraw-Hill, 2004)<em>, </em>the award winning <em>Designing and Managing the Supply Chain </em>(McGraw-Hill, 2007) and <em>The Logic of Logistics </em>(3<sup>rd</sup> edition, Springer 2013). He also wrote <em>Operations Rules: Delivering Customer Value through Flexible Operations (</em>MIT Press, 2011).</p>
<p style="text-align: justify;">Professor Simchi-Levi has consulted and collaborated extensively with private and public organizations. He was the founder of LogicTools which provided software solutions and professional services for supply chain optimization. LogicTools is now part of IBM.</p>ISE Seminar-Applying Machine Learning in Online Revenue Management
http://illinois.edu/calendar/detail/3605/32975906
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32975906Thu, 07 Apr 2016 16:00:00 CDT<p style="text-align: justify;"><strong>Abstract </strong></p>
<p style="text-align: justify;">In a dynamic pricing problem where the demand function is unknown a priori, price experimentation can be used for demand learning. In practice, however, online sellers are faced with a few business constraints, including the inability to conduct extensive experimentation, limited inventory and high demand uncertainty. In this talk we discuss models and algorithms that combine machine learning and price optimization that significantly improve revenue. We report results from live implementations at companies such as Rue La La, Groupon and a large European Airline carrier.</p>
<p style="text-align: justify;"><strong>Biography</strong></p>
<p style="text-align: justify;">David Simchi-Levi is a Professor of Engineering Systems at MIT and Chairman of OPS Rules, an operations analytics consulting company. He is considered one of the premier thought leaders in supply chain management and business analytics.</p>
<p style="text-align: justify;">His research focuses on developing and implementing robust and efficient techniques for operations management. He has published widely in professional journals on both practical and theoretical aspects of supply chain and revenue management.</p>
<p style="text-align: justify;">His Ph.D. students have accepted faculty positions in leading academic institutes including U. of California Berkeley, Columbia U., Duke U., Georgia Tech, Harvard U., U. of Illinois Urbana-Champaign, U. of Michigan, Purdue U. and Virginia Tech.</p>
<p style="text-align: justify;">Professor Simchi-Levi co-authored the books M<em>anaging the Supply Chain </em>(McGraw-Hill, 2004)<em>, </em>the award winning <em>Designing and Managing the Supply Chain </em>(McGraw-Hill, 2007) and <em>The Logic of Logistics </em>(3<sup>rd</sup> edition, Springer 2013). He also wrote <em>Operations Rules: Delivering Customer Value through Flexible Operations (</em>MIT Press, 2011).</p>
<p style="text-align: justify;">Professor Simchi-Levi has consulted and collaborated extensively with private and public organizations. He was the founder of LogicTools which provided software solutions and professional services for supply chain optimization. LogicTools is now part of IBM.</p>