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
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;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5578982