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  1. 1
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  2. 2
    SUDOKU HELPER

    SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

    Published 2015
    “…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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  3. 3
    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
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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  4. 4
    A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali

    A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali by Hilyati Hanina, Zazali

    Published 2012
    “…This approach presents better platform in finite field E as compared to the original works using the braid groups. The second algorithm deals with the use of Decomposition Problem in encryption scheme for ECC. …”
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  5. 5
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. …”
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  6. 6
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…This study presented an intelligence based genetic algorithm approach to optimize the considered problem objectives through reducing the problem complexity. …”
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  7. 7
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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  8. 8
    Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA)

    Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA) by Alamri, Hammoudeh S., Zamli, Kamal Z., Ahmad Firdaus, Zainal Abidin, Mohd Faizal, Ab Razak

    Published 2019
    “…This paper proposes Opposition-based Whale Optimization Algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. …”
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  9. 9
    Harmony annealing algorithm for curriculum-based course timetabling problem

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

    Published 2012
    “…An attempt to solve these problems was made via an approach broken down into two parts; first, constructive algorithm with saturation degree approach was used to ensure a feasible solution, where the hard constraints are satisfied.Secondly, Harmony annealing algorithm was used to further improve the results obtained.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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  10. 10
    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems

    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

    Published 2014
    “…The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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  11. 11
    Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm

    Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2024
    “…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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  12. 12
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…The performance of the MODPSO algorithm is finally validated using artificial problems from the literature and real-world problems from assembly products.…”
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  13. 13
    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. …”
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  14. 14
    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
    “…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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  15. 15
    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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  16. 16
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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  17. 17
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…These problems will occur because these fields are mainly used machine learning classifiers. …”
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  18. 18
    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
    “…This indicates the capability of the algorithm in exploring the search space. The 2S-ENDSHHMO algorithm can be used to improve the search process of other MOSI-based algorithms and can be applied to solve MOPs in applications such as structural design and signal processing.…”
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  19. 19
    A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem

    A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

    Published 2017
    “…However, literature shows that limited research has been carried out to solve theMDSQP using bioinspired algorithms. To fill this gap, this paper proposes a simple and effective solution based on genetic algorithms to solve this classical problem. …”
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  20. 20
    A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem

    A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

    Published 2017
    “…However, literature shows that limited research has been carried out to solve theMDSQP using bioinspired algorithms. To fill this gap, this paper proposes a simple and effective solution based on genetic algorithms to solve this classical problem. …”
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