Using interactive evolutionary computation (IEC) with validated surrogate fitness functions for redistricting

Authors:
Christine Chou;Steven Kimbrough;John Sullivan-Fedock;C. Jason Woodard;Frederic H. Murphy
Affiliations:
National Dong Hwa University, Hualien, Taiwan Roc;University of Pennsylvania, Philadelphia, PA, USA;University of Pennsylvania, Philadelphia, USA;Singapore Management University, Singapore, Singapore;Temple University, Philadelphia, PA, USA
Venue:
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Year:
2012

Citing 7
Cited 0

A Taxonomy for artificial embryogeny

Artificial Life
Introduction to Evolutionary Computing

Introduction to Evolutionary Computing
Applying genetic algorithms to zone design

Soft Computing - A Fusion of Foundations, Methodologies and Applications
Preface: interactive evolutionary computation

New Generation Computing
Providing an appropriate search space to solve the fatigue problem in interactive evolutionary computation

New Generation Computing
Graph partitioning through a multi-objective evolutionary algorithm: a preliminary study

Proceedings of the 10th annual conference on Genetic and evolutionary computation
A reactive GRASP for a commercial territory design problem with multiple balancing requirements

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe a novel use of evolutionary computation to discover good districting plans for the Philadelphia City Council. We were able to discover 116 distinct, high quality, legally valid plans. These constitute a rich resource on which stakeholders may base deliberation. The exercise raised 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.