tabu-search

This paper proposes a data-driven framework using graph neural networks to enhance Tabu search by predicting candidate moves' quality, improving efficiency in tactical wireless network design problems.

This paper introduces a composite-move Tabu search algorithm for spatial redistricting that improves solution quality and efficiency while preserving contiguity constraints.