DocumentCode
2214644
Title
Immune clone algorithm and mfcTP
Author
Hongwei, Zhang ; Xiaoke, Cui ; Shurong, Zou
Author_Institution
Sch. of Comput. Sci., Chengdu Univ. of Inf. Technol., Chengdu, China
Volume
1
fYear
2010
fDate
20-22 Aug. 2010
Abstract
A new immune clone algorithm is proposed for coping with the multi-objective fixed-charged transportation optimization problem (mfcTP) in the paper. In terms of this new algorithm base on the vector affinity, we firstly make the sum of active and fixed-charged order by ascending and greedy algorithm infused into the antibody decoding, sequentially enhancing the intelligent learning ability of antibody; Then apply the cloning mechanism, balanced the relationship between the global exploration and the local development and enhanced the optimization ability of the algorithm. The experimental results show that the algorithm can find better Pareto front and Pareto optimal solutions in the real-world problems even if nonlinear and discontinuous. So it is more effective than st-GA and m-GA.
Keywords
Pareto optimisation; artificial immune systems; greedy algorithms; transportation; vectors; Pareto front; Pareto optimal solutions; active order; antibody decoding; ascending algorithm; cloning mechanism; fixed-charged order; greedy algorithm; immune clone algorithm; mfcTP optimization; multiobjective fixed-charged transportation optimization; vector affinity; Production facilities; Pareto optimal solutions; Pruefer number; concentration; immune clone; vector affinity;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location
Chengdu
ISSN
2154-7491
Print_ISBN
978-1-4244-6539-2
Type
conf
DOI
10.1109/ICACTE.2010.5578982
Filename
5578982
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