Document Type : Regular Article

Authors

• Bahaa Kamal
• Nadia Al-Saidi

Department of Applied Science, University of Technology / Baghdad – Iraq

Abstract

Chaos theory has attracted much attention because it fully reflects the complexity of the system, which is an essential property in many applications, especially in the optimization problem.  In this paper, the possibility of improving research by means of evolutionary algorithms (genetic algorithms) will be discussed which used to solve non- linear programming problems. This improvement and development are carried out using a highly quality chaotic map, which was proposed to be used for generating real values (keys) that are used as reference values for the genetic algorithm. A comparison between the results without using chaotic systems and the results after generating the keys is performed. It shows that the results after the chaotic local search (CLS) are improved and congregate with the optimum value of the solutions obtained by the projected process before the CLS. Moreover, the differences between the proposed systems for improvement are also compared. The evaluation parameters for the proposed chaotic function are developed using the Mathematica 11.2 program.

Keywords

• Nonlinear programming
• evolutionary algorithm
• chaos theory

Main Subjects

• Applied Mathematics