DocumentCode
479361
Title
Intelligent Algorithms for Solving Multiobjective Optimization Problems
Author
Yi Hong-Xia ; Xiao Liu ; Liu, Xiao
Author_Institution
Inst. of Electron., Chinese Acad. of Sci., Beijing
fYear
2008
fDate
12-14 Oct. 2008
Firstpage
1
Lastpage
5
Abstract
This paper presents a comprehensive survey of many evolutionary algorithms for solving multiobjective optimization problems. Four main kinds of multiobjective algorithms (GA, PSO, SA, and AC) have been presented, and their merits and demerits are compared and discussed respectively. Finally, a mix algorithm is suggested as an effective method.
Keywords
genetic algorithms; particle swarm optimisation; simulated annealing; ant colony algorithm; evolutionary algorithm; genetic algorithm; intelligent algorithm; multiobjective optimization problem; particle swarm optimisation; simulated annealing; Ant colony optimization; Clustering algorithms; Constraint optimization; Distributed computing; Evolutionary computation; Genetic algorithms; Optimization methods; Pareto optimization; Sorting; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-2107-7
Electronic_ISBN
978-1-4244-2108-4
Type
conf
DOI
10.1109/WiCom.2008.3054
Filename
4681243
Link To Document