By Topic

Vehicle route planning with constraints using genetic algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Pellazar, M.B. ; B-2 Div., Northrop Corp., Pico Rivera, CA, USA

A route planning approach based on a class of adaptive search techniques called genetic algorithms (GAs) is presented for planning 3D routes for multiple air-vehicles through a threat dense environment. This paper describes a GA-based route planner which generates effective vehicle routes and elegantly accommodates these mission constraints. Preliminary studies on GA-based air-vehicle route planners has shown this approach to be very promising. This paper extends previous research through integration with a complete hierarchy-based mission management system. The results of several experiments are illustrated and discussed. The main thrust of these experiments focus on: (1) investigating effective configuration of classes of GA operators; (2) determining GA operator parameter settings that will produce “near-optimal” routes; (3) exploring the use of a domain-specific mutation operator, called “target bias mutation”, for expediting convergence; and (4) comparing results against the well-known dynamic programming algorithm

Published in:

Aerospace and Electronics Conference, 1994. NAECON 1994., Proceedings of the IEEE 1994 National

Date of Conference:

23-27 May 1994