Simulated Annealing for Antenna Placements

2026-10-06

AI Summary

This study addresses the geometric optimization challenge posed in the GIS Cup, which involves deploying antennas along polygon boundaries to maximize visible coverage. To tackle this problem, we propose a decoupled framework that separates geometric preprocessing from combinatorial search, extending candidate positions into edge interiors to enhance solution space exploration. A secondary objective function is introduced to guide search convergence, while an incremental position optimization strategy integrates simulated annealing, destroy-and-repair heuristics, and elitist crossover operators. Experimental evaluations across nine parameter configurations, encompassing 261 to 16,273 buildings, demonstrate substantial improvements in service threshold attainment rates. As a top-performing team, we were invited to present our findings at the competition.

Abstract

The 2026 ACM SIGSPATIAL GIS Cup posed the following geometric challenge: Given a set of simple, pair-wise disjoint polygons, compute $k$ antennas (points) on polygon boundaries, maximizing the number of polygons with at least a fraction $τ$ of their perimeter visible from the antennas. Contestants had 24 hours to produce the best possible solutions. We describe an approach that separates geometric visibility preprocessing from a portfolio of incremental combinatorial searches. A construction pool provides initial solutions with antennas restricted to polygon vertices; simulated annealing explores one-for-one antenna swaps, complemented by exact discrete one-swap descent, ruin-and-recreate, and elite crossover. A secondary objective rewards progress toward the service threshold without overriding the primary score. Candidate antennas are later expanded to include points in polygon-edge interiors. Our submitted solutions cover between 261 and 16,273 buildings across the nine parameter combinations, and the team was invited to present as one of the top entries. The code is available at https://github.com/JacobusTheSecond/giscup.

Innovation

• Simulated Annealing
• Geometric Visibility
• Combinatorial Search
• Antenna Placement
• Ruin-and-Recreate