Title: A quantum encoding bat algorithm for uninhabited combat aerial vehicle path planning

Authors: Qifang Luo; Liangliang Li; Yongquan Zhou

Addresses: College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China; Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning 530006, China ' College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China ' College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China; Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning 530006, China

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.

Keywords: bat algorithm; UCAV path planning; quantum encoding; quantum encoding bat algorithm; QBA.

DOI: 10.1504/IJICA.2017.086642

International Journal of Innovative Computing and Applications, 2017 Vol.8 No.3, pp.182 - 193

Received: 29 Jun 2016
Accepted: 06 Mar 2017
Published online: 15 Sep 2017 *

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