Search Results - (( discrete optimization methods algorithm ) OR ( parallel optimization method algorithm ))

Refine Results
  1. 1

    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. …”
    Get full text
    Get full text
    Thesis
  2. 2

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    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
    “…The strategy is based on the combination of heuristic initialization and discrete optimization methods, assisted by graph theory. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    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). …”
    Get full text
    Get full text
    Thesis
  5. 5

    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
    “…We propose a novel modification to the PSO algorithm to perform rapid discrete optimization. The proposed Discrete-PSO method (DPSO) uses a rescaling equation to convert the continuous-valued positions into discrete-valued variables. …”
    Get full text
    Get full text
    Research Reports
  6. 6

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

    Published 2024
    “…Hence, optimization algorithms, consisting of exact and heuristic methods, are crucial for a myriad of real-world applications. …”
    Get full text
    Get full text
    Thesis
  7. 7

    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
    “…Several global methods have been proposed for solving discrete optimization problems. …”
    Get full text
    Get full text
    Monograph
  8. 8

    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.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

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

    Published 2022
    “…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
    Get full text
    Get full text
    Thesis
  11. 11

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

    Published 2012
    “…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
    Get full text
    Article
  12. 12
  13. 13

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

    Published 2023
    “…Hence, this thesis will utilize Non-Systematic Weighted Random 2 Satisfiability incorporating with Binary Artificial Bee Colony algorithm in Discrete Hopfield Neural Network. The Binary Artificial Bee Colony will be utilized to optimize the logical structure according to the ratio of negative literals by capitalizing the features of the exploration mechanism of the algorithm. …”
    Get full text
    Get full text
    Thesis
  18. 18

    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. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…It is also discovered that the hybrid-discrete MOPSO (HD-MOPSO) algorithm manages to obtain higher values in the performance metrics consisting of non-dominance ratio and hypervolume compared to the competing algorithms. …”
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    A variational discrete filled function approach in discrete global optimization by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

    Published 2015
    “…Many real-life applications governed by discrete variables poss multiple local optimal solutions, which requires the utilization of global optimization tools find the best solution amongst them.The main difficulty in determining the best solution, or also known as the global solution, is to escape from the basins surrounding local minimums.To overcome this issue, an auxiliary function is introduced in discrete filled function method which turns the local minimizer of the original function become a maximizer.Then, an improved local minimum is found by minimizing the filled function, otherwise the edge of the feasible region is attained.Based on a discrete filled function method from the literature, we propose a modification particularly on the neighbourhood search to enhance its computational efficiency.Numerical results suggest that the proposed algorithm is efficient in solving large scale complex discrete optimization problems.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item