Performance analysis of artificial bee colony algorithm on ARM based mobile platform

Improved mobile devices have the computational power and software support for processing complex algorithmic expressions with the similar execution time when compared to the conventional processors. In this study, we investigated both serial and parallel implementations of Artificial Bee Colony (ABC) algorithm that is one of the most important swarm intelligence based algorithms by solving different types of numerical problems on a mobile platform. Experimental studies showed that serial and parallel implementations of ABC algorithm are suitable for execution on mobile processors and there is a correspondence between the final solutions obtained by ABC algorithm on a mobile processor and the final solutions obtained by ABC algorithm on a conventional processor.

[1]  Milan Tuba,et al.  Different approaches in parallelization of the artificial bee colony algorithm , 2011 .

[2]  Dharmender Kumar,et al.  A review on Artificial Bee Colony algorithm , 2013 .

[3]  Tiranee Achalakul,et al.  Artificial bee colony algorithm on distributed environments , 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

[4]  Hasan Badem,et al.  A new efficient training strategy for deep neural networks by hybridization of artificial bee colony and limited-memory BFGS optimization algorithms , 2017, Neurocomputing.

[5]  Selcuk Okdem,et al.  An application of Wireless Sensor Network routing based on Artificial Bee Colony Algorithm , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[6]  Selcuk Aslan,et al.  Best Supported Emigrant Creation for Parallel Implementation of Artificial Bee Colony Algorithm , 2016 .

[7]  Alper Bastürk,et al.  Parallel Implementation of Synchronous Type Artificial Bee Colony Algorithm for Global Optimization , 2012, J. Optim. Theory Appl..

[8]  Rafael Stubs Parpinelli,et al.  Parallel Approaches for the Artificial Bee Colony Algorithm , 2011 .

[9]  Harikrishna Narasimhan,et al.  Parallel artificial bee colony (PABC) algorithm , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[10]  Harish Sharma,et al.  Artificial bee colony algorithm: a survey , 2013, Int. J. Adv. Intell. Paradigms.

[11]  Dervis Karaboga,et al.  Probabilistic Dynamic Deployment of Wireless Sensor Networks by Artificial Bee Colony Algorithm , 2011, Sensors.

[12]  Selcuk Aslan,et al.  A new artificial bee colony algorithm to solve the multiple sequence alignment problem , 2016, Int. J. Data Min. Bioinform..

[13]  Turgay Batbat,et al.  Ayrık Yapay Arı Kolonisi Algoritması ile Protein Yapısı Tahmini , 2016 .

[14]  D Karaboga,et al.  A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences. , 2016, Genetics and molecular research : GMR.

[15]  Alper Bastürk,et al.  Performance analysis of the coarse-grained parallel model of the artificial bee colony algorithm , 2013, Inf. Sci..

[16]  Dervis Karaboga,et al.  Artificial bee colony algorithm , 2010, Scholarpedia.