New continuous ant colony algorithm for continuous function optimization in 2d and 3d search spaces
Dissertant
Thesis advisor
Comitee Members
Kanan, Ghassan Jaddu
al-Shaykh, Asim A. R.
Muaydi, Hasan
University
Arab Academy for Financial and Banking Sciences
Faculty
The Faculty of Information Systems and Technology
Department
Computer information systems
University Country
Jordan
Degree
Ph.D.
Degree Date
2010
English Abstract
We developed an ant-based approach algorithm, called 2D-3D Continuous Ant Colony Approach (2D-3D-CACA), for solving continuous function optimization in 2D and 3D search spaces.
Novel concepts of this algorithm that distinguish it from the other heuristics are : (1) the inclusion of a dynamic discretization representation in order to change from discrete nature to continuous one.
The developed dynamic discretization method speeds up the algorithm and allows evolution to directly consider the role of third dimension to tackle three-dimensional applications.
(2) The use of a simulated annealing-based local search approach for local optimization with the aim of improving the overall performance.
The developed 2D-3D-CACA algorithm consists of two phases, that is, the global phase, and the local phase.
The global phase provides a high quality starting solutions while the local phase operates on these quality solutions to obtain higher quality solutions.
By iterating these two phases, global optimum will be obtained.
The developed approach is tested on four benchmarks algebraic problems and one benchmark design engineering problem from literature.
The results obtained were compared with other continuous ant-related approaches and other approaches adapted for continuous optimization found in the literature.
The obtained results show the effectiveness of the developed approach.
Finally, we applied the developed approach to optimize one of the most important applications in real world space, that is, the problem of path generation cost estimation and road construction on 3D world space.
The developed approach was verified by carrying out a number of tests on artificially generated models.
These models range from simple terrain models, to complex models.
The approach has proven to be effective in over all models.
Main Subjects
Information Technology and Computer Science
Topics
No. of Pages
120
Table of Contents
Table of contents.
Abstract.
Chapter One : introduction.
Chapter Two : literature survey.
Chapter Three : review of state of the art and ant colony optimization.
Chapter Four : the developed algorithm.
Chapter Five : experimental results.
Chapter Six : conclusions and future research.
References.
American Psychological Association (APA)
Jabarah, Yusuf Hasan Fayiz. (2010). New continuous ant colony algorithm for continuous function optimization in 2d and 3d search spaces. (Doctoral dissertations Theses and Dissertations Master). Arab Academy for Financial and Banking Sciences, Jordan
https://search.emarefa.net/detail/BIM-306996
Modern Language Association (MLA)
Jabarah, Yusuf Hasan Fayiz. New continuous ant colony algorithm for continuous function optimization in 2d and 3d search spaces. (Doctoral dissertations Theses and Dissertations Master). Arab Academy for Financial and Banking Sciences. (2010).
https://search.emarefa.net/detail/BIM-306996
American Medical Association (AMA)
Jabarah, Yusuf Hasan Fayiz. (2010). New continuous ant colony algorithm for continuous function optimization in 2d and 3d search spaces. (Doctoral dissertations Theses and Dissertations Master). Arab Academy for Financial and Banking Sciences, Jordan
https://search.emarefa.net/detail/BIM-306996
Language
English
Data Type
Arab Theses
Record ID
BIM-306996
