Please welcome Dr. Golbarg Tutunchi back to the ISE Department. Dr. Tutunchi serves as a Senior Operations Research Specialist at SAS. She will discuss how she is using bi-criteria optimization to solve engineering problems.
As always refreshments are available in 428 Daniels Hall 30 minutes before the seminar begins.
Given a collection of 𝑛𝑛 locations and a symmetric measure of distance (difference) between each pair of locations, we seek to identify (select) a subset of 𝑝𝑝 locations so as to achieve two distinct objectives. The first objective is to minimize the maximum dissimilarity (i.e., distance) between the selected locations and other locations. The second objective is to maximize the minimum distance (diversity) among the selected locations themselves. Based on the relationship between the max-min diversity problem and the node packing problem, we propose an integer programming (IP) model and a corresponding incremental algorithm to find the efficient frontier for this bi-criteria optimization problem. Subsequently we use the relationship between this IP model and a corresponding set covering problem to propose effective methods for solving the former. Finally we employ the relationship between the node packing constraints and the set covering constraints to propose a new family of valid inequalities for the corresponding IP models that are potentially effective when solving these models. Through computational experiments we demonstrate the effectiveness of our proposed methods for solving relatively large instances of this bi-criteria optimization problem.
Dr. Golbarg Tutunchi got her PhD in the Industrial Engineering from NCSU in April 2016. Her PhD research was mainly focused on mixed integer programming problem, and developing mathematical models for bi-criteria location problems. In January 2013, while she was working on her dissertation under the supervision of Dr. Fathi at NCSU ISE department, she started working as a Graduate Internee at SAS at advanced analytic optimization services (AAOS) department. In December 2015, she started working as a full time employee in the same division. Currently she is a senior operations research specialist at OR/AI/ML center of excellence at SAS. Throughout the 4 years of collaboration with SAS, she got to apply her background in mixed integer programming in a variety of industries. Some of these industries are advertisement plan optimization in Media, launch revenue optimization in pharmaceutical, life cycle price optimization for large retailers and route optimization for a European transportation company. She has also continued her collaboration with her advisor and NCSU ISE department after her graduation.
