Killer Whale Algorithm: An Algorithm Inspired by the Life of Killer Whale

Totok R. Biyanto*, Matradji, Sonny Irawan, Henokh Y. Febrianto, Naindar Afdanny, Ahmad H. Rahman, Kevin S. Gunawan, Januar A.D. Pratama, Titania N. Bethiana

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

48 Citations (Scopus)


This paper proposed a new algorithm inspired by the life of Killer Whale. A group of Killer Whale called Matriline that consist of a leader and members. The leader's duty searches prey position and the optimum direction to chase the prey, meanwhile chase the prey is performed by the members. Optimum direction means minimum direction and maximum velocity. Global optimum is obtained by comparing the results of member's actions. In this algorithm, if value of objective function of members more than leader, hence the leader must find out another new potential prey. In order to obtain the performance of proposed algorithm, it is necessary to test the new algorithm together with other algorithm using known mathematical function that available in Comparing Continuous Optimizers (COCO) especially Black Box Optimization Benchmarking (BBOB). Optimization results show that the performances of purposed algorithm has outperformed than others algorithms such as Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA) and Simulated Annealing (SA).

Original languageEnglish
Pages (from-to)151-157
Number of pages7
JournalProcedia Computer Science
Publication statusPublished - 2017
Event4th Information Systems International Conference 2017, ISICO 2017 - Bali, Indonesia
Duration: 6 Nov 20178 Nov 2017


  • Algorithm
  • Benchmark
  • Killer Whale
  • Optimization


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