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Presented By: U-M Industrial & Operations Engineering

IOE Lunch & Learn Seminar Series: Marcia Fampa

The challenging Euclidean Steiner Tree Problem

U-M Industrial & Operations Engineering wordmark U-M Industrial & Operations Engineering wordmark
U-M Industrial & Operations Engineering wordmark
This event is open to all IOE graduate students and faculty. Lunch will be provided. In order to get an accurate count for food, please RSVP by noon on Wednesday, March 18.

Title: The challenging Euclidean Steiner Tree Problem

Abstract:
The Euclidean Steiner Tree Problem (ESTP) asks for a network of minimum length interconnecting a given set of points in n-dimensional space. We present well known geometric properties of the optimal solution of the ESTP and discuss their application in the development of solution methods. We focus on mixed integer nonlinear programming (MINLP) formulations and branch-and-bound algorithms, identifying characteristics of the problem that make it a big challenge in optimization, particularly when n is greater than 2. Finally, we investigate what can still be done to improve our ability to solve this problem in the broader context of MINLP.

Bio:
Marcia Fampa is a Full Professor at the Federal University of Rio de Janeiro (UFRJ), where she has been since 1997. She is at the Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), at UFRJ, where she has supervised more than 25 PhD and master students. Marcia did her undergraduate studies at the Pontifical Catholic University of Rio de Janeiro (PUC/RJ), receiving an engineering degree in 1987. She received her PhD Degree in Systems and Computer Engineering from the Federal University of Rio de Janeiro in 1996. Marcia has published a book on linear optimization, and over 50 papers in scientific journals and conferences. Her main research interest is Mixed Integer Nonlinear Programming (MINLP), with focus on the development of convex relaxations for MINLP problems.
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U-M Industrial & Operations Engineering wordmark

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