@article{(Open Science Index):https://publications.waset.org/pdf/13384,
	  title     = {Self-evolving Artificial Immune System via Developing T and B Cell for Permutation Flow-shop Scheduling Problems},
	  author    = {Pei-Chann Chang and  Wei-Hsiu Huang and  Ching-Jung Ting and  Hwei-Wen Luo and  Yu-Peng Yu},
	  country	= {},
	  institution	= {},
	  abstract     = {Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {4},
	  number    = {5},
	  year      = {2010},
	  pages     = {572 - 577},
	  ee        = {https://publications.waset.org/pdf/13384},
	  url   	= {https://publications.waset.org/vol/41},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 41, 2010},
	}