الفهرس 
Optimization ProblemsOnly 14 pages are availabe for public view
 |  | from | 121 |  |  |
| | | from | 121 | | |
Abstract
Genetic algorithm (GA and plural GAs) is a powerful tool to solve large scale design optimization problems. It is easier to use and more adaptive than other traditional optimization techniques, which need human skills and experience to set the target function(s) and rules. This thesis is interested in both theoretical improvements and introducing some applications that can be handled by the GA. On the theoretical side, an improved GA development of the applied program with the software packages Matlab is introduced. On the application side, although GA is applied to many fields to generate optimal decisions but in the thesis two fields will be handled: the first is the solution of the inverse heat equation as a mathematical application. And the other is to achieve optimal structural design in truss weight optimization as a discrete problem. This research is aimed at exploring the benefits in using the genetic algorithm to optimization fields especially the discrete one.