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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  2. 2
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  3. 3
    Evacuation routing optimizer (EROP) / Azlinah Mohamed … [et al.]

    Evacuation routing optimizer (EROP) / Azlinah Mohamed … [et al.] by Mohamed, Azlinah, Yusoff, Marina, Ariffin, Junaidah, Shamsudin, Siti Maryam

    Published 2011
    “…Solutions reached by analyses with CF random and inertia weight sorted in ascending order were shown to be competitive with those obtained using inertia weight with random capacity. …”
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  4. 4
    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem

    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem by Pook, Mei Foong, Ramlan, Effirul Ikhwan

    Published 2019
    “…Benchmarking is conducted using the traveling salesman problem. The results are comparable with the results of advanced metaheuristic algorithms. …”
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  5. 5
    Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem

    Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem by Razip, H., Zakaria, M.N.

    Published 2018
    “…We tested this approach by sampling the populations for some Set Covering Problems from OR Library using the randomized rounding method (AAR) and compared them with that sampled using a randomized heuristics (R) in terms of redundancy rate, diversity and closeness to the optimal solution (OPT). …”
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  6. 6
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  7. 7
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  8. 8
    Synchronous-asynchronous simulated kalman filter algorithm with random switching

    Synchronous-asynchronous simulated kalman filter algorithm with random switching by Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Marizan, Mubin, Norrima, Mokhtar

    Published 2020
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  9. 9
    Harmony search algorithm for curriculum-based course timetabling problem

    Harmony search algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2013
    “…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution. …”
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  10. 10
    Harmony search algorithm for curriculum-based course timetabling problem

    Harmony search algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2013
    “…However, the algorithm produced results that were not comparatively better than those previously known as best solution.With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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  11. 11
    A Kalman-Filter-Based Sine-Cosine Algorithm

    A Kalman-Filter-Based Sine-Cosine Algorithm by Mohd Falfazli, Mat Jusof, Shuhairie, Mohammad, Ahmad Azwan, Abd Razak, Ahmad Nor Kasruddin, Nasir, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Addie Irawan, Hashim

    Published 2019
    “…SKF is a random based optimization algorithm inspired from the Kalman Filter theory. …”
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  12. 12
    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems

    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad, Odili, Esther Abiodun

    Published 2016
    “…Similarly, both methods employ different search techniques in attempting solutions to the ATSP: while the African Buffalo Optimization uses the modified Karp-Steele technique, the Randomized Insertion employs random insertion mechanism. …”
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  13. 13
    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem

    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem by Odili, Julius Beneoluchi, M. N. M., Kahar, Shahid, Anwar, Azrag, M. A. K.

    Published 2015
    “…The Randomized Insertion and African Buffalo Optimization algorithms employ two different methods in attempting solutions to ATSP: the African Buffalo Optimization employs the modified Karp-Steele approach while the Randomized Insertion uses random insertion approach. …”
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  14. 14
    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

    Published 2024
    “…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. …”
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  15. 15
    A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem

    A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Zarina, M.

    Published 2021
    “…The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. …”
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  16. 16
    Comparison between Genetic Algorithm and Prey-Predator Algorithm.

    Comparison between Genetic Algorithm and Prey-Predator Algorithm. by Ong, Hong Choon

    “…In the algorithm, randomly generated solution are assigned as a predator and preys depending on their performance on the objective function. …”
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  17. 17
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  18. 18
    Opposition-based Whale Optimization Algorithm

    Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

    Published 2018
    “…The OWOA use the Opposition-based method to enhance Whale Optimization Algorithm (WOA) performance. …”
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  19. 19
    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes

    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

    Published 2020
    “…Solutions of MOGA are illustrated using the Pareto fronts. …”
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  20. 20
    Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA)

    Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA) by Nor Shuhada, Ibrahim, Nafrizuan, Mat Yahya, Saiful Bahri, Mohamed, Mohd Ismail, Yusof

    Published 2025
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