Hybrid bacterial foraging sine cosine algorithm for solving global optimization problems

• Main Authors: Shuhairie, Mohammad, Ahmad Nor Kasruddin, Nasir, Normaniha, Abd Ghani, Raja Mohd Taufika, Raja Ismail, Ahmad Azwan, Abdul Razak, Mohd Falfazli, Mat Jusof, Nurul Amira, Mhd Rizal
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2020
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/29979/1/Hybrid%20bacterial%20foraging%20sine%20cosine%20algorithm%20for%20solving.pdf; http://umpir.ump.edu.my/id/eprint/29979/; https://doi.org/10.1088/1757-899X/917/1/012081
• Institution: Universiti Malaysia Pahang

This paper proposes a new hybrid algorithm between Bacterial Foraging Algorithm (BFA) and Sine Cosine Algorithm (SCA) called Hybrid Bacterial Foraging Sine Cosine Algorithm (HBFSCA) to solve global optimization problems. The proposed HBFSCA algorithm synergizes the strength of BFA to avoid local optima with the adaptive step-size and highly randomized movement in SCA to achieve higher accuracy compared to its original counterparts. The performances of the proposed algorithm have been investigated on a set of single-objective minimization problems consist of 30 benchmark functions, which include unimodal, multimodal, hybrid, and composite functions. The results obtained from the test functions prove that the proposed algorithm outperforms its original counterparts significantly in terms of accuracy, convergence speed, and local optima avoidance.