Title: ABC_DE_FP: a novel hybrid algorithm for complex continuous optimisation problems

Authors: Parul Agarwal; Shikha Mehta

Addresses: Department of Computer Science and Engineering, Jaypee Institute of Information and Technology, Noida, India ' Department of Computer Science and Engineering, Jaypee Institute of Information and Technology, Noida, India

Abstract: Artificial bee colony (ABC) algorithm evolved as one of the efficient swarm intelligence-based algorithm in solving various global optimisation problems. Though numerous variants of ABC are available, algorithm depicts poor convergence rate in many situations. Therefore, maintaining balance between intensification and diversification of an algorithm still needs attention. In this context, a novel hybrid ABC algorithm (ABC_DE_FP) has been developed by integrating FPA and DE in original ABC algorithm. To assess the efficacy of proposed hybrid algorithm, it is primarily compared with contemporary ABC variants such as GABC, IABC and AABC over simple benchmark problems. Thereafter, it is evaluated with respect to original ABC, FPA, hybrid ABC_FP, ABC_DE and ABC_SN over CEC2014 optimisation problems for up to 100 dimensions. Results reveal that proposed algorithm considerably outperforms its counterparts in terms of minimum error value attained and convergence speed for majority of global numerical optimisation functions.

Keywords: artificial bee colony algorithm; CEC 2014 benchmark functions; nature inspired algorithms; flower pollination algorithm; FPA; differential evolution; convergence speed; complex continuous optimisation problems; minimum error value; intensification and diversification.

DOI: 10.1504/IJBIC.2019.101176

International Journal of Bio-Inspired Computation, 2019 Vol.14 No.1, pp.46 - 61

Accepted: 21 May 2018
Published online: 26 Jul 2019 *

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