2014
DOI: 10.12785/amis/080619
|View full text |Cite
|
Sign up to set email alerts
|

Artificial Bee Colony Algorithm Hybridized with Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Selection Problem

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
45
0
1

Year Published

2014
2014
2021
2021

Publication Types

Select...
4
3
3

Relationship

4
6

Authors

Journals

citations
Cited by 106 publications
(46 citation statements)
references
References 35 publications
0
45
0
1
Order By: Relevance
“…The authors propose an efficient hybrid matheuristic that combines local search and quadratic programming to solve the multi-criteria problem and obtain an approximation of the Pareto frontier. Tuba and Bacanin [2014] present a hybrid algorithm combining two population-based metaheuristics to deal with the cardinality constrained POSP. According to their results, their hybrid approach improves each of the individual approaches and also outperform the ones obtained from GA, SA, TS and PSO.…”
Section: Portfolio Optimization and Selection Problemmentioning
confidence: 99%
“…The authors propose an efficient hybrid matheuristic that combines local search and quadratic programming to solve the multi-criteria problem and obtain an approximation of the Pareto frontier. Tuba and Bacanin [2014] present a hybrid algorithm combining two population-based metaheuristics to deal with the cardinality constrained POSP. According to their results, their hybrid approach improves each of the individual approaches and also outperform the ones obtained from GA, SA, TS and PSO.…”
Section: Portfolio Optimization and Selection Problemmentioning
confidence: 99%
“…Meta-sezgisel algoritmaların orijinal versiyonları, çözüm kalitesini artırmak için modifiye edilir veya melezleştirilir. En yaygın doğadan esinlenen algoritmalar, parçacık sürü optimizasyonu (PSO) [18], diferansiyel evrim (DE) [19], ateşböceği algoritması (FA) [20], [21], guguk kuşu arama (CS) [22], karınca koloni optimizasyonu [23][24][25][26], yapay arı koloni algoritması [27][28][29][30], yarasa algoritması (BA) [31], ağaç tohum algoritması [32] …”
Section: Gi̇ri̇ş (Introduction)unclassified
“…Artificial bee colony (ABC) algorithm performs intensification and diversification processes, which are cornerstones of swarm algorithms, by utilizing employed, onlooker and scout bees. It was successfully applied to unconstrained [10], [11] and constrained benchmark problems [12], engineering problems [13] and many others [14]. In this paper we used elements of the ABC algorithm for hybridization of our proposed algorithm.…”
Section: Introductionmentioning
confidence: 99%