A Hybrid Bumble Bees Mating Optimization - GRASP Algorithm for Clustering

被引：0
|
作者：
Marinakis, Yannis [1 ]
Marinaki, Magdalene [2 ]
Matsatsinis, Nikolaos [1 ]
机构：
[1] Tech Univ Crete, Decis Support Syst Lab, Dept Prod Engn & Management, Khania 73100, Greece
[2] Tech Univ Crete, Dept Prod Engn & Management, Ind Syst Control Lab, Iraklion, Greece
来源：
HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS | 2009年 / 5572卷
关键词：
Bumble Bees Mating Optimization; Greedy Randomized Adaptive Search Procedure; Clustering Analysis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new hybrid algorithm for clustering, which is based on the concepts of the Bumble Bees Mating Optimization (BBMO) and Greedy Randomized Adaptive Search Procedure (GRASP), is presented in this paper. The proposed algorithm is a two phase algorithm which combines a new algorithm called Bumble Bees Mating Optimization algorithm for the solution of the feature selection problem and a GRASP algorithm for the solution of the clustering problem. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods using datasets from the UCI Machine Learning Repository. The high performance of the proposed algorithm is achieved as the algorithm gives very good results and in some instances the percentage of the correct. clustered samples is very high and is larger than 98%.
引用
收藏
页码：549 / +
页数：2
相关论文
共 50 条
  • [31] A MEMETIC-GRASP ALGORITHM FOR CLUSTERING
    Marinakis, Yannis
    Marinaki, Magdalene
    Matsatsinis, Nikolaos
    Zopounidis, Constantin
    ICEIS 2008: PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL AIDSS: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS, 2008, : 36 - 43
  • [32] Physiological specialization of the brain in bumble bee castes: Roles of dopamine in mating-related behaviors in female bumble bees
    Morigami, Ayaka
    Sasaki, Ken
    PLOS ONE, 2024, 19 (03):
  • [33] Honey-bees mating optimization (HBMO) algorithm:: A new heuristic approach for water resources optimization
    Bozorg-Haddad, Omid
    Afshar, Abbas
    Marino, Miguel A.
    WATER RESOURCES MANAGEMENT, 2006, 20 (05) : 661 - 680
  • [34] Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization
    Omid Bozorg Haddad
    Abbas Afshar
    Miguel A. Mariño
    Water Resources Management, 2006, 20 : 661 - 680
  • [35] Detection of Mammograms Using Honey Bees Mating Optimization Algorithm (M-HBMO)
    Durgadevi, R.
    Hemalatha, B.
    VishnuKumarKaliappan, K.
    2014 WORLD CONGRESS ON COMPUTING AND COMMUNICATION TECHNOLOGIES (WCCCT 2014), 2014, : 50 - 53
  • [36] A hybrid particle swarm optimization algorithm for clustering analysis
    Marinakis, Yannis
    Marinaki, Magdalene
    Matsatsinis, Nikolaos
    DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2007, 4654 : 241 - +
  • [37] Hybrid Reptile Search Algorithm and Remora Optimization Algorithm for Optimization Tasks and Data Clustering
    Almotairi, Khaled H.
    Abualigah, Laith
    SYMMETRY-BASEL, 2022, 14 (03):
  • [38] A Hybrid Bees Algorithm with Grasshopper Optimization Algorithm for Optimal Deployment of Wireless Sensor Networks
    Deghbouch, Hicham
    Debbat, Fatima
    INTELIGENCIA ARTIFICIAL-IBEROAMERICAL JOURNAL OF ARTIFICIAL INTELLIGENCE, 2021, 24 (67): : 18 - 35
  • [39] Generating Healthy Menus for Older Adults using a Hybrid Honey Bees Mating Optimization Approach
    Pop, Cristina Bianca
    Chifu, Viorica Rozina
    Salomie, Ioan
    Prigoana, Cristian
    Boros, Tiberiu
    Moldovan, Dorin
    2015 17TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC), 2016, : 452 - 459
  • [40] A Honey Bees Mating Optimization Algorithm with Path Relinking for the Vehicle Routing Problem with Stochastic Demands
    Marinakis, Yannis
    Marinaki, Magdalene
    SWARM INTELLIGENCE (ANTS 2018), 2018, 11172 : 423 - 424
12345