A quantum encoding bat algorithm for uninhabited combat aerial vehicle path planning. (2017)

• Record Type: Journal Article
• Authors: Luo, Qifang; Li, Liangliang; Zhou, Yongquan
• Is Part Of: International journal of innovative computing and applications. Volume 8:Number 3(2017)
• Page Start: 182
• Page End: 193
• Publication Date: 2017
• Subjects: bat algorithm -- UCAV path planning -- quantum encoding -- quantum encoding bat algorithm -- QBA; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Uninhabited combat aerial vehicle (UCAV) path planning aims to obtain an optimal or near-optimal flight path considering the different kinds of threats and constraints in the combat field. This paper proposes a novel quantum encoding bat algorithm (QBA) for solving the path planning of UCAV. Using quantum rotation and quantum NOT gate are implemented to change the basic qubit states and to enhance global search capability. The QBA can find a feasible and global path for the UCAV to avoid the threats and constraints. The experimental results show that the proposed QBA algorithm is an effective and feasible method in solving UCAV path planning problem than some well-known algorithms.