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  1. 1
    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm

    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

    Published 2019
    “…Furthermore, a case study was conducted to validate the proposed EE-ASP model and the performance of the optimisation algorithms. The MFO performance was compared with three frequently used meta-heuristics algorithms in ASP, namely Ant Colony Optimisation (ACO), Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO). …”
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  2. 2
    Security framework based multi agent system architecture to facilitate data fetching from cloud data storage

    Security framework based multi agent system architecture to facilitate data fetching from cloud data storage by Mohamed, Amir Mohamed Talib

    Published 2012
    “…Based on the evaluation of the post-survey, GSecaaS has been developed. …”
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  3. 3
    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…It is organized into three phases: preliminary investigation, implementation and analysis, and validation. The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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  4. 4
    Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

    Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions by Kian, Sheng Lim, Zuwairie, Ibrahim, Salinda, Buyamin, Anita, Ahmad, Faradila, Naim, Kamarul Hawari, Ghazali, Norrima, Mokhtar

    Published 2013
    “…Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. …”
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  5. 5
    Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions

    Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Mohd Falfazli, Mat Jusof, Kian, Sheng Lim

    Published 2014
    “…In VEPSO, each objective function is optimised by a swarm of particles under guidance of the best solution, known as leader, from another swarm. Recently, an improved VEPSO algorithm, namely VEPSO incorporated non-dominated solution (VEPSOnds), has been introduced by the use of non-dominated solution as leader. …”
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  6. 6
    Crosssover-first different evolution: a comprehensive post- Hoc analysis

    Crosssover-first different evolution: a comprehensive post- Hoc analysis by Jason Teo

    Published 2017
    “…Explore a new evolutionary optimization approach using Crossover-First Differential Evolution. Implementation details explained clearly with a comprehensive post-hoc statistical analysis to support the algorithm. …”
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  7. 7
    An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique

    An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique by Hameed, Asaad Shakir

    Published 2021
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  8. 8
    Parallel Implementation Of Field Visualizations With High Order Tetrahedral Finite Elements

    Parallel Implementation Of Field Visualizations With High Order Tetrahedral Finite Elements by Ishak, Mohammad Hafifi Hafiz

    Published 2013
    “…The method builds upon an approach of the open source visualization software VTK where the data visualizer program ParaView is freely available. By using Red Partitioning of high order elements, the implemented algorithm successfully enables visualization of up to fourth order tetrahedra while using the same data structure for second order tetrahedra as available in ParaView. …”
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  9. 9
    Performance evaluation of heuristic methods in solving symmetric travelling salesman problems

    Performance evaluation of heuristic methods in solving symmetric travelling salesman problems by Lim, Yai-Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan, Baten, Md Azizul

    Published 2016
    “…Their performances were compared and the appropriate algorithm for solving TSPs was then identified. The solution quality was evaluated using empirical testing, benchmark solutions and probabilistic analyses. …”
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  10. 10
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Yusof, Zulkifli Md., Ibrahim, Zuwairie, Adam, Asrul, Azmi, Kamil Zakwan Mohd, Ab. Rahman, Tasiransurini, Muhammad, Badaruddin, Ab. Aziz, Nor Azlina, Abd Aziz, Nor Hidayati, Mokhtar, Norrima, Shapiai, Mohd Ibrahim, Muhammad, Mohd Saberi

    Published 2018
    “…These three combinatorial SKF algorithms use binary encoding to represent the solution to a combinatorial optimization problem. …”
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  11. 11
    Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders

    Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders by Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Mohd Ibrahim, Shapiai, Marizan, Mubin, Dong, Hwa Kim

    Published 2014
    “…The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. …”
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  12. 12
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Asrul, Adam, Kamil Zakwan, Mohd Azmi, Tasiransurini, Ab Rahman, Badaruddin, Muhammad, Nor Azlina, Ab. Aziz, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Mohd Saberi, Mohamad

    Published 2018
    “…The algorithm proposed in this paper is called state-encoded distance evaluated SKF (SEDESKF) algorithm. …”
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  13. 13
    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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  14. 14
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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  15. 15
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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  16. 16
    An Improved VEPSO Algorithm for Multi-objective Optimisation Problems

    An Improved VEPSO Algorithm for Multi-objective Optimisation Problems by Kamarul Hawari, Ghazali, Zuwairie, Ibrahim, Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Sophan Wahyudi, Nawawi, Norrima, Mokhtar

    Published 2015
    “…Multi-objective optimisation problem is the problem which contains more than one objective that needs to be solved simultaneously. The vector evaluated particle swarm optimisation algorithm is widely used for such purpose, where this algorithm optimised one objective using one swarm of particles by the guidance from the best solution found by another swarm. …”
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  17. 17
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  18. 18
    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar

    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

    Published 2015
    “…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. The post-islanding frequency stability is maintained by optimizing the Load Frequency Control‘s parameters. …”
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  19. 19
    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
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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  20. 20
    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…Furthermore, we used the Pareto dominance concept after calculating the value of crowding degree for each solution. …”
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