DocumentCode :
3274885
Title :
Flight Path Planning Based on an Improved Genetic Algorithm
Author :
Ji Xiao-Ting ; Xie Hai-Bin ; Zhou Li ; Jia Sheng-De
Author_Institution :
Nat. Univ. of Defense Technol., Changsha, China
fYear :
2013
fDate :
16-18 Jan. 2013
Firstpage :
775
Lastpage :
778
Abstract :
Flight path planning for UAV is a complicated optimization problem with multiple constrains. In this paper, an improved dual-population genetic algorithm (IDPGA) is proposed. It uses an additional population to maintain population diversity of genetic algorithm (GA). The two populations have different evolutionary objectives and thus use different fitness functions. Generating offspring of each population is performed by randomly generating new individuals, inbreeding between individuals in the same population and crossbreeding between individuals from different populations. The next generation is produced by selecting the best ones from current populations and offspring. Besides, in order to improve the convergence performance of the algorithm, the initial populations are generated based on multiple constraints. The experimental results show that IDPGA improves the global search and local search capabilities for GA to ensure the global optima of the flight path.
Keywords :
autonomous aerial vehicles; convergence; genetic algorithms; path planning; search problems; IDPGA; UAV; convergence performance; evolutionary objectives; fitness functions; flight path planning; global search; improved dual-population genetic algorithm; local search; multiple constrains; optimization problem; population diversity; Genetic algorithms; Genetics; Next generation networking; Path planning; Planning; Sociology; Statistics; an improved dual-population genetic algorithm; crossbreeding; flight path planning; inbreeding; maintain population diversity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
Type :
conf
DOI :
10.1109/ISDEA.2012.184
Filename :
6455830
Link To Document :
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