Using Interactive Evolutionary Computation (IEC) with Validated Surrogate Fitness Functions for Redistricting

Christine CHOU
Steven O. KIMBROUGH
John SULLIVAN-FEDOCK
C. Jason WOODARD, Singapore Management University
Frederic H. MURPHY

Abstract

We describe a novel use of evolutionary computation to discover good districting plans for the Philadelphia City Council. We discovered 116 distinct, high quality, legally valid plans. These constitute a rich resource for stakeholders to base deliberation. This raises the issue of how to deal with large numbers of plans, especially with the aim of avoiding gerrymandering and promoting fairness. Interactive Evolutionary Computation (IEC) is a natural approach here, if practicable. The paper proposes development of Validated Surrogate Fitness (VSF) functions as a workable and generalizable form of IEC.