Genetic algorithm based path planner
Dissertant
University
University of Technology
Faculty
-
Department
Computer Sciences Department
University Country
Iraq
Degree
Ph.D.
Degree Date
1998
English Abstract
There are many combinatorial optimization problems for which t lie re is no direct or efficient method of solution.
Genetic Algorithm (1A) is one of the most promising techniques for solving such large optimization problems.
It is a robust search and optimization strategy based on the principles of natural gene lies and survive} of the fittest.
One of the most important subjects to consider when applying GA is the choice of the presentation scheme.
It is a pivotal factor that decides (at early stages) the worthiness and efficiency of Hoe GA approach in solving a given problem.
It is on these bases that current research is developed.
The study presented here reports the initial experiments that have been undertaken oil a program of work whose aim is the development of a unit genetic-based path planning system.
Seeking "good" representation, and on the base of chromosome length, two different schemes of varying complexity are presented, accompanied with relative setups, restrictions, and performance criteria.
To tackle the ambiguities involved, the present work is adapted to the robotics domain.
Experiments are thus performed with the purpose of evaluating the potential of applying GA to optimize the generation of path plans for robot navigation through cluttered environment.
Compared with traditional search strategies, genetic search gave results which have shown that (regardless of the approached schemes), even behavior is hard to predict, GA comprises a powerful adaptive planning mechanism, mid with multiple constrained optimization, it provide solid foundation to perform sustained search for the optimal (or even near optimal) solution in the most promising parts of the search.
Main Subjects
Information Technology and Computer Science
Topics
American Psychological Association (APA)
al-Bayati, Maha Adham. (1998). Genetic algorithm based path planner. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-306319
Modern Language Association (MLA)
al-Bayati, Maha Adham. Genetic algorithm based path planner. (Doctoral dissertations Theses and Dissertations Master). University of Technology. (1998).
https://search.emarefa.net/detail/BIM-306319
American Medical Association (AMA)
al-Bayati, Maha Adham. (1998). Genetic algorithm based path planner. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-306319
Language
English
Data Type
Arab Theses
Record ID
BIM-306319
