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  1. 1
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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  2. 2
    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning

    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

    Published 2019
    “…GWO-HS was evaluated using 24 classical benchmark functions with 30 state-of-the-art benchmark functions from CEC2014. …”
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  3. 3
    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin

    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin by Mohamad Husnin, Shahirah Atikah

    Published 2018
    “…These methods were tested with several selected functions by using code Maple 18 software. The numerical analysis shows a strong evidence that the smBFGS is more efficient than the mBFGS method. …”
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  4. 4
    Feature fusion using a modified genetic algorithm for face and signature recognition system

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…A modified fitness function in Wrapper GA was introduced by adding a function to maintain the balanced of the selected features. …”
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  5. 5
    Modified Opposition Based Learning to Improve Harmony Search Variants Exploration

    Modified Opposition Based Learning to Improve Harmony Search Variants Exploration by Al-Omoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2020
    “…Harmony Search Algorithm (HS) is a well-known optimization algorithm with strong and robust exploitation process. …”
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  6. 6
    Common benchmark functions for metaheuristic evaluation: a review

    Common benchmark functions for metaheuristic evaluation: a review by Hussain, Kashif, Mohd Salleh, Mohd Najib, Shi, Cheng, Naseem, Rashid

    Published 2017
    “…In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. …”
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  7. 7
    Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm

    Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm by Abu Samah, Khyrina Airin Fariza

    Published 2016
    “…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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  8. 8
    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin

    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin by Jinudin, Muhammad Imza Fakhri

    Published 2018
    “…All algorithms are written and executed using Maple 16 software. …”
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  9. 9
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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  10. 10
    Methodology for modified whale optimization algorithm for solving appliances scheduling problem

    Methodology for modified whale optimization algorithm for solving appliances scheduling problem by Omar, Mohd Faizal, Mohd Bakeri, Noorhadila, Mohd Nawi, Mohd Nasrun, Hairani, Norfazlirda, Khalid, Khalizul

    Published 2020
    “…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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  11. 11
    Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms

    Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2018
    “…HS algorithm has been modified to handle the 0/1 Knapsack problem, such as adding penalty function to cope the weight condition, exclude the harmony search bandwidth (bw) parameter, and use the current best result in the next iteration to obtain a better result. …”
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  12. 12
    A modified technique in RFID networking planning and optimization

    A modified technique in RFID networking planning and optimization by Nawawi, Azli

    Published 2015
    “…In this research, PSO algorithm was used in the optimization process as it was considered as a very useful, efficient and well known algorithm. …”
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  13. 13
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Since, ANFIS use fuzzy logic, the model accuracy is highly dependent on selecting the appropriate type of membership function. …”
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  14. 14
    An application of improved salp swarm algorithm for optimal power flow solution considering stochastic solar power generation

    An application of improved salp swarm algorithm for optimal power flow solution considering stochastic solar power generation by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2023
    “…The iSSA's performance was tested on a modified IEEE 30-bus system and compared to other recent algorithms, including SSA. …”
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  15. 15
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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  16. 16
    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…To simulate the DC motor system with a PI-PD controller that was optimized by several swarm intelligence algorithms, MATLAB/Simulink software was utilized. …”
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  17. 17
    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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  18. 18
    Loss minimization of optimal power flow with stochastic solar power generation using improved salp swarm algorithm

    Loss minimization of optimal power flow with stochastic solar power generation using improved salp swarm algorithm by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2022
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  19. 19
    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.

    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

    Published 2020
    “…Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems. …”
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  20. 20
    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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