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  1. 1
    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application

    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application by Tan, Jia Zheng

    Published 2018
    “…The solution for C=681 use 49.7% of the total hardware resources in pure hardware and it is 1.09 times faster than pure hardware and 1.42 times faster than pure software. …”
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    Monograph
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  2. 2
    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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    Thesis
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  3. 3
    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi

    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

    Published 2015
    “…Twenty one benchmark-instances have been modified for this case and solved by using the aforesaid algorithms. Afterward, the TTRPSD is extended by considering the time window constraints. …”
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  4. 4
    Parallel metaheuristic algorithm for route planning using CUDA

    Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

    Published 2025
    “…This research aims to significantly speed up solution searching for the TSP by using GPUs compared to CPUs. …”
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    Final Year Project / Dissertation / Thesis
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  5. 5
    Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm

    Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

    Published 2022
    “…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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  6. 6
    Improvement DACS3 Searching Performance using Local Search

    Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2009
    “…The capability of DACS3 is measured based on quality of solution, time taken to reach the solution and algorithm performance. …”
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    Conference or Workshop Item
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  7. 7
    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
    “…Furthermore, the accuracy of the state estimate with the smallest state error covariance is enhanced by using the Kalman filtering theory. This enhancement produces the filtering solution by using the second sub-algorithm. …”
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  8. 8
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  9. 9
    Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli

    Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli by Zulkifli, Nadea Suneeza

    Published 2017
    “…The solution that had being used is three-dimensional array chromosome structure to represent each schedule. …”
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  10. 10
    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem

    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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  11. 11
    Optimized crossover genetic algorithm for vehicle routing problem with time windows

    Optimized crossover genetic algorithm for vehicle routing problem with time windows by Nazif, Habibeh, Lee, Lai Soon

    Published 2010
    “…Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. …”
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  12. 12
    A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time

    A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time by Nazif, Habibeh, Lee, Lai Soon

    Published 2009
    “…For this problem, we propose a genetic algorithm using an optimised crossover operator designed by an undirected bipartite graph to find an optimal schedule which minimises the total weighted completion time of the jobs in the presence of the sequence independent family setup times. …”
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  13. 13
    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan

    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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  14. 14
    Comparison Between Linear Programming And Integer Linear Programming: A Review

    Comparison Between Linear Programming And Integer Linear Programming: A Review by Sam, Mei Lee, Saptari, Adi, Salleh, Mohd Rizal, Mohamad, Effendi

    Published 2018
    “…Meanwhile, heuristics outperform exact algorithms in solving large sized problem where it can obtain near optimal solution in an acceptable computational time. …”
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  15. 15
    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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  16. 16
    Developing class scheduler system / Mohamed Imran Mohamed Ariff

    Developing class scheduler system / Mohamed Imran Mohamed Ariff by Mohamed Ariff, Mohamed Imran

    Published 2006
    “…This algorithm has been proven to come out with faster solutions that the standard sequential time-tabling algorithms.…”
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    Research Reports
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  17. 17
    Developing a college room allocation system using heuristic algorithm / Raziha Bidin

    Developing a college room allocation system using heuristic algorithm / Raziha Bidin by Bidin, Raziha

    Published 2010
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  18. 18
    Improving Class Timetabling using Genetic Algorithm

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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  19. 19
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…The paper conducts design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. …”
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    Proceeding Paper
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  20. 20
    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…The unsupervised solution using time series clustering algorithms is capable to extract valuable information and identify structure in complex and massive datasets as spatial time series. …”
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