Hybrid bacterial foraging sine cosine algorithm for solving global optimization problems

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 opt...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: 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
التنسيق: Conference or Workshop Item
اللغة:English
منشور في: IOP Publishing 2020
الموضوعات:
الوصول للمادة أونلاين: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
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الوصف
الملخص: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.