Multi-Objective Optimization Based on Brain Storm Optimization Algorithm

In recent years, many evolutionary algorithms and population-based algorithms have been developed for solving multi-objective optimization problems. In this paper, the authors propose a new multi-objective brain storm optimization algorithm in which the clustering strategy is applied in the objectiv...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of swarm intelligence research Ročník 4; číslo 3; s. 1 - 21
Hlavní autoři: Shi, Yuhui, Xue, Jingqian, Wu, Yali
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hershey IGI Global 01.07.2013
Témata:
Algorithms
Clustering
Evolutionary algorithms
Multiple objective analysis
Optimization
Solution space
ISSN:1947-9263, 1947-9271
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In recent years, many evolutionary algorithms and population-based algorithms have been developed for solving multi-objective optimization problems. In this paper, the authors propose a new multi-objective brain storm optimization algorithm in which the clustering strategy is applied in the objective space instead of in the solution space in the original brain storm optimization algorithm for solving single objective optimization problems. Two versions of multi-objective brain storm optimization algorithm with different characteristics of diverging operation were tested to validate the usefulness and effectiveness of the proposed algorithm. Experimental results show that the proposed multi-objective brain storm optimization algorithm is a very promising algorithm, at least for solving these tested multi-objective optimization problems.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ISSN:1947-9263
1947-9271
DOI:10.4018/ijsir.2013070101