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. 2012:2012:418946.
doi: 10.1100/2012/418946. Epub 2012 Dec 27.

A bat algorithm with mutation for UCAV path planning

Gaige Wang  1 , Lihong Guo, Hong Duan, Luo Liu, Heqi Wang
Affiliations

A bat algorithm with mutation for UCAV path planning

Gaige Wang et al. ScientificWorldJournal. 2012.

Abstract

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

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Figures

Figure 1
Figure 1
Coordinates transformation relation.
Figure 2
Figure 2
Modeling of the UCAV threat cost [6].
Algorithm 1
Algorithm 1
Bat Algorithm.
Algorithm 2
Algorithm 2
Algorithm of BA for UCAV path planning.
Algorithm 3
Algorithm 3
Bat algorithm with mutation.
Algorithm 4
Algorithm 4
Algorithm of BAM for UCAV path planning.
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