3d terrain visualization and CPU parallelization of particle swarm optimization

Abstract

Particle Swarm Optimization is a bio-inspired optimization technique used to approximately solve the non-deterministic polynomial (NP) problem of asset allocation in 3D space, frequency, antenna azimuth [1], and elevation orientation [1]. This research uses QT Data Visualization to display the PSO solutions, assets, transmitters in 3D space from the work done in [2]. Elevation and Imagery data was extracted from ARCGIS (a geographic information system (GIS) database) to add overlapping elevation and imagery data to that the 3D visualization displays proper topological data. The 3D environment range was improved and is now dynamic; giving the user appropriate coordinates based from the ARCGIS latitude and longitude ranges. The second part of the research improves the performance of the PSOs runtime, using OpenMP with CPU threading to parallelize the evaluation of the PSO by particle. Lastly, this implementation uses CPU multithreading with 4 threads to improve the performance of the PSO by 42% - 51% in comparison to running the PSO without CPU multithreading. The contributions provided allow for the PSO project to be more realistically simulate its use in the Electronic Warfare (EW) space, adding additional CPU multithreading implementation for further performance improvements.