International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 4, No. 10, 8 Sep. 2012
Cover page and Table of Contents: PDF (size: 315KB)
Hybrid Flow Shop Scheduling Problem Using Artificial Immune System
Full Text (PDF, 315KB), PP.82-88
Views: 0 Downloads: 0
Author(s)
Index Terms
Artificial Immune System, Hybrid Flow Shop, Combinatorial Optimization
Abstract
Artificial immune system (AIS) is a new technique for solving combinatorial optimization problems. AIS are computational systems that explore, describe and apply different mechanisms inspired by biological immune system in order to solve problems in different domains. In this paper, we propose an algorithm based on the principle of clonal selection and affinity maturation mechanism in an immune response used to solve the Hybrid Flow Shop (FSH) scheduling problem. The parameters in this kind of algorithm play an important role in the quality of solutions in one hand and computer time (CPU) needed another hand. The experimental results have shown the influence of these parameters.
Cite This Paper
Mustapha GUEZOURI, Abdelkrim HOUACINE, "Hybrid Flow Shop Scheduling Problem Using Artificial Immune System", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.10, pp.82-88, 2012. DOI:10.5815/ijisa.2012.10.09
Reference
[1]A. BONDAL, "Artificial Immune Systems Applied to Job Shop Scheduling", Thesis For the degree Master of Science, Faculty of The Russ College of Engineering and Technology of Ohio University, USA, March 2008.
[2]Jason Brownlee, "Clonal Selection Theory & The Clonal Selection Classification Clonalg Algorithm (CSCA)", Technical Report No. 2-02, Centre for Intelligent Systems and Complex Processes (CPSIC), Faculty of Information & Communication Technologies (ICT), Swinburne University of Technology (SUT), Melbourne, Australia, 2005 .
[3]Jason Brownlee, "A Taxonomy of Artificial Immune Coarse Systems", Technical Report TR2006-01 ICT, SUT, Melbourne, Australia.2006 .
[4]Leandro N. De Castro, and Fernando J. Von Zuben, "Learning and Optimization Using The Clonal Selection Principle", IEEE Transactions on Evolutionary Computation, Special Issue on Artificial Immune Systems, vol. 6, n. 3, pp. 239-251, 2002.
[5]O. Engin*, A. Döyen, "Artificial Immune Systems And Applications In Industrial Problems", Selçuk Üniversitesi Mühendislik-Mimarlık Fak. Endüstri Mühendisliği Bölümü, Alaeddin Keykubad Kampüsü, Selçuklu, Konya, TÜRKİYE. Vol. 17, pp. 71-84, 2004.
[6]Mokhtar GHARBI, "Optimization through artificial immune system", Internship Report Master 2 IFSIC CERV: European Centre Reality Virtuelle.2006.
[7]M. Gourgand, N. Grangean and S. NORR, " A contribution to the stochastic flow shop scheduling problem ", Laboratory of Informatics, Modeling and Optimization of Systems, University Blaise Pascal, Clermont Ferrand II, France, Volume 151, Issue 2, 1 December 2003, Pages 415–433, 2003.
[8]H. Gao and X. Liu , "Improved Artificial Immune Algorithm and its application on the Permutation flow Shop Sequencing Problems ", Software Engineering Institute, Xidian University , China, Vol. 6, pp. 929-933, 2007.
[9]Emmanuel NERON, " Du Flow Shop Hybride au Problème Cumulatif ", Ph.D. Thesis, University of Technology of Compiègne Laboratory HEUDIASYC, UMR CNRS 6599, July 2005.
[10]Ruben Ruiz, José Antonio Rodríguez-ÁZQUEZ, "The Hybrid Flow Shop Scheduling Problem", School of Computer Science, University of Nottingham Jubilee Campus Wollaton Road, Nottingham, Volume 205, Issue1,Pages1–18,August2010.
[11]A. Vignier, "Contribution to solving scheduling problems of single phase type, multi-machine (Hybrid Flow Shop)", PhD thesis, University of Tours, 1997.
[12]Andrew Watkins, Xintong Bi, and Amit Phadke, "Parallelizing an Immune-Inspired Algorithm for Efficient Pattern Recognition," Intelligent Engineering Systems through Artificial Neural Networks: Smart Engineering System Design: Neural Networks, pp. 225-230, 2003.