Composite-move Tabu search expands neighborhoods in redistricting optimization by moving minimal connected sets of units identified via graph articulation points, yielding better solutions and efficiency than standard Tabu search.
International Journal of Geographical Information Science 33, 368–384
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
XFlowMap introduces cross-scale flow pattern detection using scan statistics, automated generalization, and a novel multi-attribute flow symbol for mapping massive OD data.
MODEE is a multimodal system that integrates graphs with LLM embeddings to outperform prior open-domain event extraction methods on large datasets.
The study applies data preprocessing and pattern analysis to public transit records as preparation for ML-based digital twin modeling of urban mobility.
citing papers explorer
-
Fast and Effective Redistricting Optimization via Composite-Move Tabu Search
Composite-move Tabu search expands neighborhoods in redistricting optimization by moving minimal connected sets of units identified via graph articulation points, yielding better solutions and efficiency than standard Tabu search.
-
XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data
XFlowMap introduces cross-scale flow pattern detection using scan statistics, automated generalization, and a novel multi-attribute flow symbol for mapping massive OD data.
-
A Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents
MODEE is a multimodal system that integrates graphs with LLM embeddings to outperform prior open-domain event extraction methods on large datasets.
-
Unveiling Urban Mobility Patterns: A Data-Driven Analysis of Public Transit
The study applies data preprocessing and pattern analysis to public transit records as preparation for ML-based digital twin modeling of urban mobility.