AIML Journal

Volume 06 - Issue 1

ICGST

A Comparison between Genetic Algorithms and Sequential Quadratic Programming in Solving Constrained Optimization Problems
Alaa Sheta, HamzaTurabieh
Information Technology Department, Prince Abdullah Bin Ghazi Faculty of Science and Information Technology,
Al-Balqa Applied University, Al-Salt, Jordan.

Abstract:

There are variety of problems in mechanical, electrical, chemical and aerospace engineering that can be formulated as NonLinear Programming (NLPs). The quality of the developed solution significantly affect the performance of such systems. In this paper, we investigate the ability of Genetic Algorithms (GAs) to tackle the constrained NLPs problems. Experimental results indicated that GAs can effectively solve these types of problems. GAs can overcome many problems encountered by traditional search techniques as gradient based methods. The performance of GAs is compared to the Sequential Quadratic Programming (SQP) method.

Keywords: Constraint Optimization, Genetic Algorithms, Quadratic Sequential Programming, Industrial Processes.

(Full Paper 428 KB)

Biography:

Alaa Sheta received his B.S., M.S. degrees in Electronics and Communication Engineering from Faculty of Engineering, Cairo University in 1988 and 1994, respectively. A. Sheta received his Ph.D. degree from the Computer Science Department, School of Information Technology, George Mason University, Fairfax, VA, USA. Currently, Dr. Sheta is working with the Information Technology Department, Prince Abdullah Bin Ghazi Faculty of Science and Information Technology, Al-Balqa Applied University, Al-Salt, Jordan since October 2004. He is also the Dean Assistant for Planning and Development since October 2006. His research interests include Modelling and Simulation of Dynamical Nonlinear Systems, Robotics, Evolutionary Computation, Automatic Control, Fuzzy Logic, and Neural Networks. Dr. Sheta served as a chair or co-chair for number of workshops and special session within international conferences in the area of Computer Science and Engineering. He has been an invited speaker in number of national and international conference.

Hamza I. Turabieh received the B.A degree in Information Technology from Al-Balqa Applied University, and M.S degree in Computer Science from Al-Balqa Applied University in 2000 and 4004, respectively. He worked as a Technical Support Assistant at the General Computers and Electrical Company, Amman, Jordan. Currently, he is an Assistant Researcher with the Information Technology Department, Prince Abdullah Bin Ghazi Faculty of Science and Information Technology, Al-Balqa Applied University. His research interests include Artificial Intelligence, Evolutionary Computation and Image Processing.

BibTex:

@ARTICLE{P1120548003,

AUTHOR = {Alaa Sheta and HamzaTurabieh},

TITLE = {A Comparison between Genetic Algorithms and Sequential Quadratic Programming in Solving Constrained Optimization Problems},

JOURNAL = {The International Journal of Artificial Intelligence and Machine Learning},

YEAR = {2006},

VOLUME = {6},

ISSUE ={1},

PAGES={67--74}

}

(Full Paper 428 KB)