Research Article Open Access

An Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data Clustering

Ibrahim Al-Marashdeh1, Ghaith M. Jaradat2, Masri Ayob3, Ahmad Abu-Al-Aish2 and Mutasem Alsmadi1
  • 1 Imam Abdurrahman Bin Faisal University, Saudi Arabia
  • 2 Jerash University, Jordan
  • 3 National University of Malaysia, Malaysia


This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into enhancing the BB-BC’s effectiveness in clustering data. Where, the inclusion of an elite pool alongside implicit solution recombination and local search method, contribute to such enhancement. Such strategies resulted in a balanced search of good quality population that is also diverse. The proposed elite pool-based BB-BC was compared with the original BB-BC and other identical metaheuristics. Fourteen different clustering datasets were used to test BB-BC and the elite pool-based BB-BC showed better performance compared to the original BB-BC. BB-BC was impacted more by the incorporated strategies. The experiments outcomes demonstrate the high quality solutions generated by elite pool-based BB-BC. Its performance in fact supersedes that of identical metaheuristics such as swarm intelligence and evolutionary algorithms.

Journal of Computer Science
Volume 14 No. 12, 2018, 1611-1626


Submitted On: 24 February 2018 Published On: 19 June 2018

How to Cite: Al-Marashdeh, I., Jaradat, G. M., Ayob, M., Abu-Al-Aish, A. & Alsmadi, M. (2018). An Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data Clustering. Journal of Computer Science, 14(12), 1611-1626.

  • 19 Citations



  • Big Bang-Big Crunch Metaheuristic
  • Elite Pool
  • Implicit Recombination
  • Euclidean Distance
  • Data Clustering