Wednesday 24th of April 2024
 

Multi-Objective Evolutionary Computation Solution for Chocolate Production System Using Pareto Method


Alaa Sheta, Abdel Karim Baareh, Mohamed Ababna and Noor Khrisat

Solving manufacturing engineering problems normally involves variety of challenges. It is important to maximize profit, improve quality of a product mean while reduce losses and cost. This trade-off plays a vita role in solving many manufacturing optimization problem. The Chocoman Inc, USA produces varieties of chocolate bars, candy and wafer by means of raw materials. The objective of the company is to minimize its cost while maximizing the production of eight products. The formulation of this problem resulted in five functions to be optimized based twenty nine constraints to be satisfied. This is a typical Multi-objective Optimization Problems (MOPs). Many methods attempted to solve this problem. In this paper, we provide a comparison between the Scalarization and Pareto methods based Genetic Algorithms (GAs) to solve the chocolate production problem. GAs provides an outstanding solution.

Keywords: Multi-objective Optimization Problems (MOPs), Evolutionary Computation, Chocolate Production System, Scalarization Method, Pareto Method, GEATbx, Matlab

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ABOUT THE AUTHORS

Alaa Sheta
Alaa F. Sheta received his B.E., M.Sc. degrees in Electronics and Communication Engineering from Faculty of Engineering, Cairo University in 1988 and 1994, respectively. He received his Ph.D. degree from the Computer Science Department, School of Information Technology and Engineering, George Mason University, Fairfax, VA, USA in 1997. Currently, Prof. Sheta is a faculty member with the Computer Science Department, The World Islamic Sciences and Education (WISE) University, Amman, Jordan. He is on leave from the Electronics Research Institute (ERI), Cairo, Egypt. He published over 80 papers, book chapters and two books in the area of image processing and evolutionary computations. He has been an invited speaker in number of national and international conferences. Prof. Sheta is a member of the IEEE Evolutionary Computations, ACM and ISAI societies. He is also the Vice President of the Arab Computer Society (ACS). His research interests include Evolutionary Computation, Modeling and Simulation of Dynamical Nonlinear Systems, Image Processing, Robotics, Swarm Intelligence, Automatic Control, Fuzzy Logic, Neural Networks and Software Reliability Modeling.

Abdel Karim Baareh
Abdel Karim Baareh received his B.Sc degree in Science from Mysore University India in 1992, completed a Post Graduate Diploma in Computer Application PGDCA from Mysore University India in 1993. He received his Master in Computer Application (MCA) from Bangalore University India in 1999. He received his Ph.D. in Informatics from Damascus University, Syria in 2008. Currently, Dr. Baareh is a faculty member with the Computer Science Department, Al-Balqa’a Applied University, Ajloun College, Jordan. He is the Chairman of the Applied Science Department at Ajloun College since 2009. His research interest includes Neural Networks, Fuzzy Logic, Image Processing and Genetic Algorithms

Mohamed Ababna
Mohammad F. Ababneh received his Ph.D. in Computer Engineering from Cairo University, Egypt. Currently he is Associate Professor with the Computer Science Department and the Dean of the Faculty of Information Technology, Al-Balqa\'a Applied University, Jordan. His research interest includes Artificial Intelligence, Computer Network, Virtual Reality, and Image Processing. Dr. Ababneh has been a program committee member for many national and international conferences. He is an active member for many national computer science societies.

Noor Khrisat
Information Technology Department, Al-Balqa Applied University


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