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  1. 1
    A random search based effective algorithm for pairwise test data generation

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…Java program has been used to test the performance of the algorithm. …”
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  2. 2
    EasyA: Easy and effective way to generate pairwise test data

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…Java program has been used to test the performance of the algorithm. …”
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  3. 3
    Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin

    Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

    Published 2019
    “…The system architecture which consists of a user interface, web framework and storage data. D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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  4. 4
    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider

    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider by Omer Fadlelmola Elkhider, Samih

    Published 2011
    “…In this dissertation a mobile cloud will be under consideration when designing the prototype, it is proven that mobile processors are tiny processors and could only handle a limited resources, thus the ability of making the applications processes in server, leaving the mobile clients a small part of only accessing data and interact with it. Such methodology can be achieved by java programming language for mobile clients J2ME, and by using a second generation mobile phones. …”
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  5. 5
    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing

    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

    Published 2012
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  6. 6
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. …”
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  7. 7
    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems

    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems by N. M., Yahya, Tokhi, M. O.

    Published 2017
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  8. 8
    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems

    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems by Fayaz, Muhammad, Arshad, S, Shah, A.S, Shah, Asadullah

    Published 2016
    “…The proposed algorithm is simple and efficient than the other heuristic algorithms for the MVC problem. …”
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  9. 9
    A population division based multi-task sine cosine algorithm for test redundancy reduction optimization

    A population division based multi-task sine cosine algorithm for test redundancy reduction optimization by Kamal Z., Zamli, Kader, Md Abdul, Mekeng, Ambros Magnus Rudolf

    Published 2024
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  10. 10
    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
    “…The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.…”
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  11. 11
    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity

    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity by Ahmad Azwan, Abdul Razak

    Published 2019
    “…On the other hand, multi-objective algorithm is applicable to solve a problem with two or more objectives. …”
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  12. 12
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
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  13. 13
    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
    “…This project has the capability to reduce the execution time of application problem using parallel algorithms to increase efficiency of cluster computing. …”
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  14. 14
    Towards Software Product Lines Optimization Using Evolutionary Algorithms

    Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

    Published 2019
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  15. 15
    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems

    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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  16. 16
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
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  17. 17
    Modified adaptive bats sonar algorithm with doppler effect mechanism for solving single objective unconstrained optimization problems

    Modified adaptive bats sonar algorithm with doppler effect mechanism for solving single objective unconstrained optimization problems by N. A., Azlan, Nafrizuan, Mat Yahya

    Published 2019
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  18. 18
    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement

    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”
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  19. 19
    Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases

    Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases by Hafeez, Ahmad

    Published 2021
    “…However, the performance of the classical location and scatter estimators is usually flawed by singularity and outliers’ problems in high dimensional data sets. The study aimed to modify the existing ML test by incorporating the Cholesky banded regularization methods and thresholding sample covariance matrix to resolve singularity problems and incorporating the L₁-median with Weiszfeld’s algorithm (MLw) covariance matrix to solve outliers’ problem in high dimensional data sets. …”
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  20. 20
    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
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