Optimization Meets Politics: Mathematical Models and a Practical Case Study in Political Redistricting - Rahul Swamy, UIUC, 11/10/2023
From Thiago Serra
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From Thiago Serra
Over
the last century, Operations Research (O.R.)
has transformed numerous public sector domains such as healthcare and
defense. This talk dives into how O.R. models such as integer
programming can benefit democratic processes, particularly in redrawing
political district boundaries. In the U.S., state legislative
and congressional district boundaries are redrawn every ten years to
account for population shifts. The precise way these lines are drawn
affects who will likely get elected and affects electoral
representation. This talk presents optimization models and algorithms
that incorporate fairness into this map-drawing process,
motivated by well-established political science research. Beyond these
models, this talk features a case study in Arizona that explores
practical considerations. These considerations include trade-offs
between redistricting criteria such as compactness and competitiveness,
achieving near-equal population balance, and computational
intractability when solving large input sizes. These models and methods
serve as starting points for achieving fairness and transparency
in future redistricting cycles where computers are expected to play a
greater role than ever.
Rahul
is an Operations Research and Data Science
professional. He has a Ph.D. in Operations Research from the University
of Illinois at Urbana-Champaign, an M.S. in Operations Research from
SUNY Buffalo and a B.S. in Engineering Physics from the Indian Institute
of Technology Madras. His Ph.D. thesis at
UIUC explored political redistricting, a complex national problem with
electoral consequences, through the lens of large-scale optimization
modeling and heuristic design. He has prioritized practical
implementation and mathematical rigor in his optimization
work, resulting in publications such as Operations Research, INFORMS Journal on Optimization,
Journal of Combinatorial Optimization, and INFORMS Journal on Applied Analytics.
Presently, he is a Senior Data Scientist at Walmart Centroid,
optimizing Walmart's large-scale supply chain and transportation
strategy.