DocumentCode :
2559891
Title :
An adaptive multi-objective bacterial swarm optimzer
Author :
Xu, Xin ; Liu, Yan-heng ; Wang, Ai-min ; Wang, Gang ; Chen, Hui-ling
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
812
Lastpage :
816
Abstract :
This paper proposes an adaptive multi-objective bacterial swarm optimizer (AMBSO) for multi-objective problems. The proposed AMBSO method implements the search for Pareto optimal set of multi-objective optimization problems. The AMBSO has been compared with the MBFO over a test suite of five ZDT numerical benchmarks with respect to the two performance measures: Generational Distance and Diversity Measure. The simulation results show that the AMBSO is able to find a much better Pareto front solutions.
Keywords :
Pareto optimisation; biology; microorganisms; numerical analysis; AMBSO; Pareto front solutions; Pareto optimal set; ZDT numerical benchmarks; adaptive multiobjective bacterial swarm optimizer; diversity measurement; generational distance; multiobjective optimization problems; Benchmark testing; Delta modulation; Educational institutions; Kernel; Microorganisms; Optimization; Standards; Bacterial foraging optimzer; Multi-objective optimization; Pareto front;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234713
Filename :
6234713
Link To Document :
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