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  1. 1
    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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  2. 2
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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  3. 3
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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  4. 4
    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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  5. 5
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Based on the experimental results, the proposed optimized discrete DA has a higher effectiveness than the adapted discrete DA when the performance of the algorithms is compared in terms of both iteration number and computation cost. …”
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  6. 6
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. …”
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  7. 7
    Modification of particle swarm optimization algorithm for optimization of discrete values

    Modification of particle swarm optimization algorithm for optimization of discrete values by Mohd Yassin, Ahmad Ihsan, Jusoh, Muhammad Huzaimy, Abdul Rahman, Farah Yasmin

    Published 2011
    “…The SIP test suite is a set of seven real-life discrete numerical engineering problems, and is a common benchmark for discrete optimization algorithms.…”
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  8. 8
    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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  9. 9
    A modified discrete filled function algorithm for solving nonlinear discrete optimization problems

    A modified discrete filled function algorithm for solving nonlinear discrete optimization problems by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan

    Published 2012
    “…The discrete filled function method is a global optimization tool for searching for best solution amongst multiple local optima.This method has proven useful for solving large-scale discrete optimization problems.In this paper, we consider a standard discrete filled function algorithm in the literature and then propose a modification to increase its efficiency.…”
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  10. 10
    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)

    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408) by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

    Published 2016
    “…Most practical discrete and mixed discrete optimization problems are nonlinear and known to have more than one locally optimal solution. …”
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  11. 11
    Multi-state PSO GSA for solving discrete combinatorial optimization problems

    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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  12. 12
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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  13. 13
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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  14. 14
    A novel multi-state gravitational search algorithm for discrete optimization problems

    A novel multi-state gravitational search algorithm for discrete optimization problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  15. 15
    An improved multi-state particle swarm optimization for discrete combinatorial optimization problems

    An improved multi-state particle swarm optimization for discrete combinatorial optimization problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  16. 16
    A discrete simulated kalman filter optimizer for combinatorial optimization problems

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…However, these extensions may result in increased execution times for the algorithm. In this research, a new combinatorial algorithm named discrete simulated Kalman filter optimizer (DSKFO) is proposed to solve combinatorial optimization problem. …”
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  17. 17
    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem

    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem by Ismail, Ibrahim, Hamzah, Ahmad, Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Kamal, Khalil, Muhammad Arif, Abdul Rahim

    Published 2014
    “…The binary-based algorithms including the binary particle swarm optimization (BPSO) algorithm are proposed to solve discrete optimization problems. …”
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  18. 18
    Mine blast algorithm for optimization of truss structures with discrete variables

    Mine blast algorithm for optimization of truss structures with discrete variables by Sadollah, Ali, Bahreininejad, A., Eskandar, Hadi, Abd Shukor, Mohd Hamdi

    Published 2012
    “…The efficiency of the proposed optimizer is tested via the optimization of several truss structures with discrete variables and its performance is compared with several well-known metaheuristic algorithms. …”
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  19. 19
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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  20. 20
    Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization

    Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization by Zuwairie, Ibrahim

    Published 2014
    “…PSO is a population based stochastic optimization algorithm, inspired by the social behavior of bird flocking and fish schooling. …”
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