Table of Contents Author Guidelines Submit a Manuscript
Applied Computational Intelligence and Soft Computing
Volume 2012, Article ID 560184, 16 pages
Research Article

Using Genetic Algorithms for Navigation Planning in Dynamic Environments

1Center of Research for Advanced Technologies of Informatics and Security (TÜBİTAK BILGEM), 41470 Kocaeli, Turkey
2Computer Engineering Department, Istanbul Technical University, 34469 Istanbul, Turkey

Received 25 April 2012; Revised 29 July 2012; Accepted 31 July 2012

Academic Editor: Tzung P. Hong

Copyright © 2012 Ferhat Uçan and D. Turgay Altılar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Navigation planning can be considered as a combination of searching and executing the most convenient flight path from an initial waypoint to a destination waypoint. Generally the aim is to follow the flight path, which provides minimum fuel consumption for the air vehicle. For dynamic environments, constraints change dynamically during flight. This is a special case of dynamic path planning. As the main concern of this paper is flight planning, the conditions and objectives that are most probable to be used in navigation problem are considered. In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. The evolutionary dynamic navigation planning algorithm is developed for compensating the existing deficiencies of the other approaches. The existing fully dynamic algorithms process unit changes to topology one modification at a time, but when there are several such operations occurring in the environment simultaneously, the algorithms are quite inefficient. The proposed algorithm may respond to the concurrent constraint updates in a shorter time for dynamic environment. The most secure navigation of the air vehicle is planned and executed so that the fuel consumption is minimum.