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  1. 1
    Tree Physiology Optimization tuning rule for Proportional-Integral control

    Tree Physiology Optimization tuning rule for Proportional-Integral control by Halim, A.H., Ismail, I.

    Published 2017
    “…This paper presents a tuning correlation for Proportional-Integral (PI) controller parameters using Tree Physiology Optimization algorithm (TPO). …”
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  2. 2
    Single and Multiple variables control using Tree Physiology Optimization

    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. …”
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  3. 3
    A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem

    A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem by WATADA, J., ROY, A., LI, J., WANG, B., WANG, S.

    Published 2020
    “…Moreover, the GA can quickly reach the global optima and can search without becoming stuck to the local optimal. Additionally, by choosing desirable initialization of parameters, the proposed algorithm reaches the optimum with higher accuracy. …”
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  4. 4
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  5. 5
    Parallel metaheuristic algorithm for route planning using CUDA

    Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

    Published 2025
    “…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
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  6. 6
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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  7. 7
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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    Thesis
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  8. 8
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  9. 9
    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)

    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU) by Mohd Johar, Fauzi, Azmin, Farah Ayuni, Suaidi, Mohd Kadim, Shibghatullah, Abdul Samad, Ahmad, Badrul Hisham, Salleh, Siti Nadzirah, Abdul Aziz, Mohd Zainol Abidin, Md Shukor, Mahfuzah

    Published 2013
    “…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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  10. 10
    Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review

    Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

    Published 2024
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  11. 11
    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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  12. 12
    A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR) Algorithm

    A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR) Algorithm by Udayanti, Erika Devi, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Nugroho, Fajar Agung

    Published 2012
    “…In order to find a reducts, a such applications of rough set uses a discernibility matrix. Ant Swarm Optimization Rough Reducts (ASORR) algorithm is used in rough reducts calculation for identifying significant attribute set optimally. …”
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  13. 13
    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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  14. 14
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  15. 15
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  16. 16
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…They have to be optimized for parallel execution while some parts still do have sequential execution due to data dependencies, which makes the optimization problem two folds, parallel and serial. …”
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    Research Report
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  17. 17
    A parallel prevention algorithm for black hole attacks in MANET

    A parallel prevention algorithm for black hole attacks in MANET by Yaakub, Abdul Razak, Ghathwan, Khalil I.

    Published 2015
    “…In this paper, we propose a parallel algorithm for MANETs that optimizes both routing discovery and security in an Ad Hoc On Demand Distance Vector (AODV). …”
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  18. 18
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  19. 19
    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad

    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad by Saima Gulzar, Ahmad

    Published 2017
    “…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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  20. 20
    Migrating Birds Optimization based Strategies for Pairwise Testing

    Migrating Birds Optimization based Strategies for Pairwise Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2015
    “…For pairwise testing, test cases are designed to cover all possible pair combinations of input parameter values at least once. In this paper, we investigate the adoption of Migrating Birds Optimization (MBO) algorithm as a strategy to find an optimal solution for pairwise test data reduction. …”
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