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  1. 1
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  2. 2
    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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  3. 3
    Ringed seal search for global optimization via a sensitive search model / Younes Saadi

    Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

    Published 2018
    “…The quality of the algorithm is comprehensively evaluated on various standard benchmark test functions using variety of quality metrics and using three baseline algorithms for comparison. …”
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  4. 4
    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy

    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

    Published 2014
    “…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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  5. 5
    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm

    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm by Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Nor Rul Hasma, Abdullah, Zainah, Md. Zain, Indra, Riyanto

    Published 2018
    “…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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  6. 6
    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems

    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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  7. 7
    A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization

    A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization by Jarrah, Muath Ibrahim, Mohamad Jaya, Abdul Syukor, Mohd Abid, Mohd Asyadi Azam, Alqattan, Zakaria N., Azam, Mohd Asyadi, Abdullah, Rosni, Jarrah, Hazim, Abu‑Khadrah, Ahmed Ismail

    Published 2020
    “…Therefore, researchers extensively try to improve methods of solving complex optimization problems. Many SI search algorithms are widely applied to solve such problems. …”
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  8. 8
    Transform of Artificial Immune System algorithm optimization based on mathematical test function

    Transform of Artificial Immune System algorithm optimization based on mathematical test function by Yaw M.W., Chong K.H., Kamil K.

    Published 2023
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  9. 9
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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  10. 10
    Hybrid of firefly algorithm and pattern search for solving optimization problems

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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  11. 11
    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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  12. 12
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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  13. 13
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  14. 14
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  15. 15
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  16. 16
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  17. 17
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  18. 18
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…The cuckoo search algorithm (CSA) is used in this study for optimizing WNNs. …”
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  19. 19
    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan

    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan by Misnan, Azizi

    Published 1997
    “…A depth - first search algorithm is used to search for optimal chaining. …”
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  20. 20
    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems

    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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