A Glowworm Swarm Optimization Algorithm for Uninhabited Combat Air Vehicle Path Planning

Journal of Intelligent Systems 24 (1):69-83 (2015)
  Copy   BIBTEX

Abstract

Uninhabited combat air vehicle path planning is a complicated, high-dimension optimization problem. To solve this problem, we present in this article an improved glowworm swarm optimization algorithm based on the particle swarm optimization algorithm, which we call the PGSO algorithm. In PGSO, the mechanism of a glowworm individual was modified via the individual generation mechanism of PSO. Meanwhile, to improve the presented algorithm’s convergence rate and computational accuracy, we reference the idea of parallel hybrid mutation and local search near the global optimal location. To prove the performance of the proposed algorithm, PGSO was compared with 10 other population-based optimization methods. The experiment results show that the proposed approach is more effective in UCAV path planning than most of the other meta-heuristic algorithms.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 76,199

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Optimization and improvement. [REVIEW]Paul Weirich - 2010 - Philosophical Studies 148 (3):467 - 475.
Improved FCM Algorithm Based on K-Means and Granular Computing.Zhuang Zhi Yan & Wei Jia Lu - 2015 - Journal of Intelligent Systems 24 (2):215-222.
Structure optimization of reservoir networks.Benjamin Roeschies & Christian Igel - 2010 - Logic Journal of the IGPL 18 (5):635-669.

Analytics

Added to PP
2017-01-11

Downloads
20 (#565,307)

6 months
1 (#448,894)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references