Title :
Multiobjective optimization using dynamic neighborhood particle swarm optimization
Author :
Hu, Xiaohui ; Eberhart, Russell
Author_Institution :
Dept. of Biomed. Eng., Purdue Univ., West Lafayette, IN, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper presents a particle swarm optimization (PSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives. Several benchmark cases were tested and showed that PSO could efficiently find multiple Pareto optimal solutions
Keywords :
Pareto distribution; evolutionary computation; optimisation; dynamic neighborhood particle swarm optimization; multiobjective optimization; multiple Pareto optimal solutions; one-dimension optimization; particle memory updating; Benchmark testing; Biomedical computing; Biomedical engineering; Design optimization; Equations; Evolutionary computation; Genetic algorithms; Pareto optimization; Particle swarm optimization;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004494
