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Finalist MCDM Awards 2019-2020

https://connect.informs.org/multiple-criteria-decision-making/awards/new-item

At the 2019 Annual INFORMS Annual Meeting, Clemson Mathematical Sciences alumnus Brian Dandurand, was recognized as a Finalist for the 2019 Multi-Criteria Decision Making (MCDM) Junior Researcher Best Paper Award for the paper entitled “Quadratic scalarization for decomposed multiobjective optimization,” published in OR Spectrum, 38(4):1071-1096 (2016).

Practical applications in multidisciplinary engineering design, business management, and military planning require distributed solution approaches for computing efficient decisions for systems performing under conflict and modeled as nonconvex multiobjective optimization problems. Under this motivation, Brian develops a theory and algorithms with the goal to preserve decomposable structures of such systems while addressing nonconvexity in a manner that avoids a high degree of nonlinearity and the introduction of nonsmoothness.

Brian earned a PhD degree in Mathematical Sciences at Clemson in 2013 working with Dr. Margaret Wiecek. He has hold postdoctoral positions at the Royal Melbourne Institute of Technology in Australia and the Argonne National Laboratory. He is currently on the faculty in the Department of Computer Science at the University of Wisconsin-Eau Claire.


At the 2020 Annual INFORMS Annual Meeting, Clemson Mathematical Sciences alumnus Garrett Dranichak was recognized as a Finalist for the 2020 Multi-Criteria Decision Making (MCDM) Junior Researcher Best Paper Award for the paper entitled “On highly robust efficient solutions to uncertain multiobjective linear programs,” published in European Journal of Operational Research, 273(1):20-30 (2019).  

In this paper, Garrett addresses decision making problems in the presence of conflict and uncertainty, which are encountered in many areas of human activity. He models these problems as multiobjective linear programs with uncertain objective functions coefficients and seeks robust efficient solutions, that is, decisions that are efficient in all uncertain scenarios.  

Garrett received his PhD in Mathematical Sciences from Clemson in 2018 working with Dr. Margaret Wiecek. Since his graduation he has been working as an Operations Research Analyst at Sandia National Laboratories.