{"title":"Chaotic Cuckoo Search Algorithm for Solving Unmanned Combat Aerial Vehicle Path Planning Problems","authors":"Jeng-Shyang Pan, Jenn-Long Liu, Shou-Cheng Hsiung","doi":"10.1145/3318299.3318310","DOIUrl":null,"url":null,"abstract":"This paper applies an improved Cuckoo Search algorithm, named Chaotic CS algorithm, to solve Unmanned Combat Aerial Vehicle (UCAV) path planning problems. A circle-type chaotic map for generating chaotic sequences is used to specify the scaling factor (() of step size and fraction probability (pa) of abandonment for host nests formulated in the Original CS algorithm. The advantage of using Chaotic CS algorithm can dynamically change the parameters of ( and pa by using the chaotic sequences over the course of iterations, resulting in an improvement for searching performance to find out the global best solution. The enhanced CS algorithm shows flexible and robust capabilities to optimize complex and multimodal objective functions by evaluating standard benchmark functions. Furthermore, the Chaotic CS algorithm is applied to solve complex design problem. Two scenarios of UCAV path planning problems are carried out for the practical applications. The simulation results indicate that the Chaotic CS algorithm can efficiently be used for computing optimal flight path of UCAV.","PeriodicalId":164987,"journal":{"name":"International Conference on Machine Learning and Computing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318299.3318310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
This paper applies an improved Cuckoo Search algorithm, named Chaotic CS algorithm, to solve Unmanned Combat Aerial Vehicle (UCAV) path planning problems. A circle-type chaotic map for generating chaotic sequences is used to specify the scaling factor (() of step size and fraction probability (pa) of abandonment for host nests formulated in the Original CS algorithm. The advantage of using Chaotic CS algorithm can dynamically change the parameters of ( and pa by using the chaotic sequences over the course of iterations, resulting in an improvement for searching performance to find out the global best solution. The enhanced CS algorithm shows flexible and robust capabilities to optimize complex and multimodal objective functions by evaluating standard benchmark functions. Furthermore, the Chaotic CS algorithm is applied to solve complex design problem. Two scenarios of UCAV path planning problems are carried out for the practical applications. The simulation results indicate that the Chaotic CS algorithm can efficiently be used for computing optimal flight path of UCAV.