Date of Award

August 2020

Document Type


Degree Name

Master of Science (MS)


School of Mathematical and Statistical Sciences

Committee Member

Margaret Wiecek

Committee Member

Matthew Saltzman

Committee Member

Yuyuan Ouyang


In robust multiobjective optimization, a new robustness gap is defined in [4]. This gap measures the minimal distance between the robust Pareto set and the Pareto sets of all scenarios. Upper and lower bounds of this gap are derived for the convex case. In this thesis, a deeper examination into the definition and application of this gap for uncertain multiobjective linear programs is presented. Numerical examples are developed and results are reported for the first time.



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