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  1. 1
    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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  2. 2
    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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  3. 3
    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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  4. 4
    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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  5. 5
    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
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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  6. 6
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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  7. 7
    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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  8. 8
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  9. 9
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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  10. 10
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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  11. 11
    Protein Conformantional Search Using Bees Algorithm

    Protein Conformantional Search Using Bees Algorithm by Bahamish, Hesham Awadh A., Abdullah, Rosni, Salam, Rosalina Abdul

    Published 2008
    “…To this end, an energy function is used to calculate its energy and a conformational search algorithm is used to search the conformational search space to find the lowest free energy corformation.…”
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  12. 12
    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems

    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

    Published 2016
    “…The AGC loop is used to minimize the frequency deviation and control the power exchange in order to maintain them at their scheduled values due to the changes of the step-load disturbance. The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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  13. 13
    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod

    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod by Mahmod, Nurzaima

    “…The scope of this paper is to optimize the DNA sequences alignment on the matrix rilling module by implementing a parallel method of the Smith-Waterman algorithm. …”
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  14. 14
    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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  15. 15
    Enhancing the cuckoo search with levy flight through population estimation

    Enhancing the cuckoo search with levy flight through population estimation by Mohd Nawi, Nazri, Shahuddin, Shah Liyana, Rehman, Muhammad Zubair, Khan, Abdullah

    Published 2016
    “…The algorithm is tested on five benchmark functions such as Ackley function, Griewank function, Rastrigin function, Rosenbrock function and Schwefel function. …”
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  16. 16
    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using ASIC design flow / Nurzaima Mahmod

    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using ASIC design flow / Nurzaima Mahmod by Mahmod, Nurzaima

    Published 2010
    “…The scope of this paper is to optimize the DNA sequences alignment on the matrix filling module by implementing a parallel method of the SmithWaterman algorithm. …”
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  17. 17
    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
    “…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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  18. 18
    Assessing the symbiotic organism search variants using standard benchmark functions

    Assessing the symbiotic organism search variants using standard benchmark functions by Nurul Asyikin, Zainal, Fakhrud, Din, Kamal Z., Zamli

    Published 2019
    “…Symbiotic Organism Search (SOS) is one of the latest meta-heuristic algorithms created to solve optimization problems. …”
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  19. 19
    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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  20. 20
    Application Of Genetic Algorithms For Robust Parameter Optimization

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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