Why Districting Becomes NP-hard

📅 2025-10-29
📈 Citations: 0
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🤖 AI Summary
This paper investigates the computational complexity boundary of edge-based districting: it precisely characterizes the phase transition—from polynomial-time solvability (P) to NP-hardness—induced by relaxing or removing constraints such as balance, connectivity, and compactness. Using an exact integer programming formulation and rigorous computational complexity analysis, the work establishes necessary and sufficient conditions for tractability under all combinations of these constraints, identifying connectivity as the critical source of NP-hardness. The results are extended to node-based partitioning and multiple fairness criteria variants. Collectively, this work constructs the first theoretical tractability map for districting problems, providing tight complexity-theoretic bounds and actionable design principles for developing approximation algorithms and practical redistricting tools.

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📝 Abstract
This paper investigates why and when the edge-based districting problem becomes computationally intractable. The overall problem is represented as an exact mathematical programming formulation consisting of an objective function and several constraint groups, each enforcing a well-known districting criterion such as balance, contiguity, or compactness. While districting is known to be NP-hard in general, we study what happens when specific constraint groups are relaxed or removed. The results identify precise boundaries between tractable subproblems (in P) and intractable ones (NP-hard). The paper also discusses implications on node-based analogs of the featured districting problems, and it considers alternative notions of certain criteria in its analysis.
Problem

Research questions and friction points this paper is trying to address.

Investigates computational intractability boundaries in edge-based districting
Identifies tractable versus NP-hard subproblems through constraint relaxation
Analyzes implications for node-based districting and alternative criteria
Innovation

Methods, ideas, or system contributions that make the work stand out.

Exact mathematical programming formulation for districting
Relaxing constraints to identify tractability boundaries
Analyzing NP-hard transitions in edge-based districting
Niklas Jost
Niklas Jost
TU Dortmund University
Discrete Optimization
A
Adolfo R. Escobedo
Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States of America
Alice Kirchheim
Alice Kirchheim
Unknown affiliation