Area Optimal Polygonization Using Simulated Annealing

Nir Goren, Efi Fogel, Dan Halperin

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

We describe a practical method to find near-optimal solutions for the area-optimal simple polygonization problem: Given a set of points S in the plane, the objective is to find a simple polygon of minimum or maximum area defined by S. Our approach is based on the celebrated metaheuristic Simulated Annealing. The method consists of a modular pipeline of steps, where each step can be implemented in various ways and with several parameters controlling it. We have implemented several different algorithms and created an application that computes a polygon with minimal (or maximal) area. We experimented with the various algorithmic options and with the controlling parameters of each algorithm to tune up the pipeline. Then, we executed the application on each of the benchmark instances, exploiting a grid of servers, to obtain near optimal results.

Original languageEnglish
Article number2.3
JournalJournal of Experimental Algorithmics
Volume27
Issue number2
DOIs
StatePublished - 4 Mar 2022

Funding

FundersFunder number
Blavatnik Computer Science Research Fund
US-Israel-BSF2019754
Yandex Machine Learning Initiative for Machine Learning
National Science Foundation
Israel Science Foundation1736/19
Israel Science Foundation
Tel Aviv University
Ministry of Science and Technology, Israel103129
Ministry of Science and Technology, Israel

    Keywords

    • Computational geometry
    • algorithm engineering
    • area optimization
    • exact algorithms
    • geometric optimization
    • polygonization

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