Soft Computing

, Volume 22, Issue 22, pp 7587–7603 | Cite as

An improvement in fruit fly optimization algorithm by using sign parameters

  • Ahmet BabalıkEmail author
  • Hazim İşcan
  • İsmail Babaoğlu
  • Mesut Gündüz
Methodologies and Application


The fruit fly optimization algorithm (FOA) has been developed by inspiring osphresis and vision behaviors of the fruit flies to solve continuous optimization problems. As many researchers know that FOA has some shortcomings, this study presents an improved version of FOA to remove with these shortcomings in order to improve its optimization performance. According to the basic version of FOA, the candidate solutions could not take values those are negative as well as stated in many studies in the literature. In this study, two sign parameters are added into the original FOA to consider not only the positive side of the search space, but also the whole. To experimentally validate the proposed approach, namely signed FOA, SFOA for short, 21 well-known benchmark problems are considered. In order to demonstrate the effectiveness and success of the proposed method, the results of the proposed approach are compared with the results of the original FOA, results of the two different state-of-art versions of particle swarm optimization algorithm, results of the cuckoo search optimization algorithm and results of the firefly optimization algorithm. By analyzing experimental results, it can be said that the proposed approach achieves more successful results on many benchmark problems than the compared methods, and SFOA is presented as more equal and fairer in terms of screening the solution space.


Swarm intelligence Continuous optimization Signed fruit fly optimization algorithm Benchmark function 



The authors wish to thank the Scientific Project Coordinatorship at Selcuk University and the Scientific and Technological Research Council of Turkey for their institutional supports

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all authors included in the study. This manuscript does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Ahmet Babalık
    • 1
    Email author
  • Hazim İşcan
    • 1
  • İsmail Babaoğlu
    • 1
  • Mesut Gündüz
    • 1
  1. 1.Department of Computer Engineering, Faculty of EngineeringSelcuk UniversityKonyaTurkey

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