Title :
A Ε-domination Based Multi-objective Particle Swarm Optimization
Author :
Wang, Junnian ; Liu, Lanxia ; Liu, Deshun ; Yan, Yiduo
Author_Institution :
Sch. of Inf. & Electr. Eng., Hunan Univ. of Sci. & Technol., Xiangtan, China
Abstract :
A multi-objective particle swarm optimization algorithm based on Ε-dominance is proposed. The Ε-dominance is applied to update the external set in order to obtain the Pareto set with better distribution, and the dynamic adjustment strategy, which made the algorithm achieving the search and approximation to the Pareto set, is adopted in the iterative process of the Ε-Pareto solution set. Three benchmark cases were tested and the results show that this algorithm is much more efficient than the DNPSO.
Keywords :
Pareto optimisation; iterative methods; particle swarm optimisation; set theory; Ε-Pareto solution set; Ε-domination based multiobjective particle swarm optimization; dynamic adjustment strategy; iterative process; Constraint optimization; Electric variables measurement; Evolutionary computation; Genetic algorithms; Iterative algorithms; Manufacturing automation; Mechatronics; Pareto optimization; Particle measurements; Particle swarm optimization; Ε-dominance; Multi-objective optimization; Pareto set; particle swarm optimization;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.797
