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  1. 1

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…This project will focusing on the method used to solve an optimization problem, the limitation of the method used and the results of solving flow shop sequencing problem using genetic algorithm method. …”
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    Undergraduates Project Papers
  2. 2

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
    “…Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. …”
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    Article
  3. 3

    Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2018
    “…The results obtained are competitive to previous HS variants that used to solve Knapsack problem.…”
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    Article
  4. 4

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

    Published 2022
    “…Two types of analysis are used to evaluate the proposed algorithm. First, the DSKFO algorithm is used to solve the travelling salesman problem (TSP), and then the algorithm's execution time is measured. …”
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    Thesis
  5. 5

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…An adaptive bats sonar algorithm is proposed for solving single objective optimisation problems. …”
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    Thesis
  6. 6

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

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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    Thesis
  7. 7

    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…One classical engineering problem known as the welded beam structure problem is used to test the proposed LSMA algorithm's efficacy. …”
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    Conference or Workshop Item
  8. 8

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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    Conference or Workshop Item
  9. 9

    Shuffled frog leaping algorithm for solving economic load dispatch problem / Mohammad Ariffin Aizat Ezanee by Ezanee, Mohammad Ariffin Aizat

    Published 2015
    “…Shuffled Frog Leaping Algorithm (SFLA) is proposed to solve Economic Load Dispatch (ELD) problem. …”
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    Thesis
  10. 10

    Solving transcendental equation using genetic algorithm / Masitah Hambari by Masitah , Hambari

    Published 2004
    “…This project studies the potential of using Genetic Algorithm and develops a program in order to solve Transcendental Equation in optimizing problem domain. …”
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    Thesis
  11. 11

    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
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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    Article
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    Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review by See, Phen Chiak, Wong, Kuan Yew

    Published 2008
    “…In recent years, there is an increasing interest in solving QAPs using the general extension of heuristic methods called metaheuristics. …”
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    Article
  14. 14

    Solving multi-task optimization problems using the sine cosine algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2022
    “…Often, optimization problems are solved using metaheuristic algorithms which provide good enough solution within reasonable execution time and limited resources. …”
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    Conference or Workshop Item
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    Genetic-local hybrid optimizer for solving advance layout problem by Taha, Imad, Ibrahim Habra, Hind Saleem

    Published 2006
    “…Results show the potentiality of the proposed algorithm in solving the problem and outperforming previous algorithms.…”
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    Article
  18. 18

    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem by Hasan, Mohammad Khatim

    Published 2008
    “…These new parallel and sequential finite difference time domain (FDTD) algorithms yield from O(h2), ordinary O(h4) and weighted average O(h4) centered difference discretization using direct-domain and temporary-domain are used to solve problems mentioned above. …”
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    Thesis
  19. 19

    Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

    Published 2022
    “…Multidimensional Knapsack Problem (MKP) has been widely used to model real-life combinatorial problems. …”
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    Thesis
  20. 20

    Simulated annealing algorithm for solving chambering student-case assignment problem by Ghazali, Saadiah, Abdul Rahman, Syariza

    Published 2015
    “…The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased.This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem.The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. …”
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    Conference or Workshop Item