Genetic algorithm with adaptive immigrants for dynamic flight path planning

Xiaowei Fu, Xiaoguang Gao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

Dynamic flight path planning is an important part of UAV mission planning, and it turns out to be a dynamic optimization problem. In this paper, a dynamic flight path planning model is built up. We propose an adaptive immigrant scheme genetic algorithm for this path planning problem. This algorithm could combine the random immigrant scheme and elitism-based immigrant scheme adaptively according to the number of feasible candidate solutions in the current population, and improve the diversity and convergence of GAs. Simulation studies show that the algorithm has good performance in finding near-optimal, obstacles-free paths in dynamically changing environments.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Pages630-634
Number of pages5
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010 - Xiamen, China
Duration: 29 Oct 201031 Oct 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Volume1

Conference

Conference2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Country/TerritoryChina
CityXiamen
Period29/10/1031/10/10

Keywords

  • Adaptive immigrants
  • Dynamic flight path planning
  • Elistism-based immigrants
  • Genetic algorithm
  • Random immigrants

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