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  1. 1
    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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  2. 2
    Long term energy demand forecasting based on hybrid, optimization: Comparative study

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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  3. 3
    Simulated annealing for solving economic dispatch problem / Wan Khairulizuan Wan Ismail

    Simulated annealing for solving economic dispatch problem / Wan Khairulizuan Wan Ismail by Wan Ismail, Wan Khairulizuan

    Published 2010
    “…The algorithm is demonstrated by its application to a test system. …”
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  4. 4
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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    Final Year Project / Dissertation / Thesis
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  5. 5
    OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

    OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM by Abang Ahmad Latif, Abang Sarbini

    Published 2023
    “…The outcome of this project is to maximise the efficiency of a HEV model in MATLAB-Simulink by considering fuel efficiency as the objective function. …”
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    Final Year Project Report / IMRAD
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  6. 6
    Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm

    Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm by Mohd Tholaat, Muhammad Ali Husaini

    Published 2015
    “…Thus, Genetic Algorithm is applied to solve multiple objective solar-irrigation system optimization. …”
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  7. 7
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  8. 8
    Smart Routing For Solid Waste Collection

    Smart Routing For Solid Waste Collection by Ngiam, John Tze

    Published 2023
    “…This project aims to design and develop a route optimization and decision support system for solid waste collection in Malaysia. …”
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    Final Year Project Report / IMRAD
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  9. 9
    Dynamic obstacle handling in multi-robot coverage

    Dynamic obstacle handling in multi-robot coverage by Tay, Wing Le

    Published 2024
    “…The impacts of the modified algorithm’s parameters on simulation results were also studied to determine the optimal parameters for achieving better performance. …”
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  10. 10
    Model predictive control on fed-batch penicillin fermentation process

    Model predictive control on fed-batch penicillin fermentation process by Chew, Li Mei

    Published 2009
    “…In this research study the development of optimization strategies for a fed-batch penicillin fermentation process using model predictive controller was simulated using MATLAB 7.1 software. …”
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    Undergraduates Project Papers
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  11. 11
    Optimised multi-robot path planning via smooth trajectory generation

    Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

    Published 2024
    “…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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  12. 12
    Modeling the powder compaction process using the finite element method and inverse optimization

    Modeling the powder compaction process using the finite element method and inverse optimization by Hrairi, Meftah, Chtourou, Hedi, Gakwaya, Augustin, Guillot, Michel

    Published 2011
    “…Thus, an integrated simulation module consisting of an inverse optimization method and a finite element method was developed for modeling the powder compaction process as a whole. …”
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  13. 13
    Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System

    Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System by Abd Rahman, Azira

    Published 2020
    “…An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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  14. 14
    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching

    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

    Published 2014
    “…The project is divided to several steps; in which the first step is to develop a conceptual model which can be used to generate both synthetic historical data and also simulated data. …”
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  15. 15
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

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    Monograph
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  16. 16
    Artificial neural network and inverse solution method for assisted history matching of a reservoir model

    Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

    Published 2017
    “…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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  17. 17
    Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi

    Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi by Mohammadi, Maryam

    Published 2015
    “…Metaheuristic approaches namely genetic algorithm, particle swarm optimization, artificial bee colony, simulated annealing, and imperialist competitive algorithm are adopted for the optimization procedures. …”
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  18. 18
    PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate

    PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate by Muhammad Farith Nazreen, Abu Samah, Muhamad Sukri, Hadi, Abdul Malek, Abdul Wahab, Nadzirah, Mohd Mokhtar, Intan Zaurah, Mat Darus

    Published 2022
    “…However, the lightweight structure causes undesired vibrations on a system that could damage the structure. This paper proposes a modelling of horizontal flexible plate structure by utilizing bird mating optimizer algorithm and implementation of vibration control on the system in simulation environment. …”
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  19. 19
    Energy Management Strategy and Capacity Planning of an Autonomous Microgrid: A Comparative Study of Metaheuristic Optimization Searching Techniques

    Energy Management Strategy and Capacity Planning of an Autonomous Microgrid: A Comparative Study of Metaheuristic Optimization Searching Techniques by Bukar A.L., Tan C.W., Lau K.Y., Toh C.L., Ayop R., Dahiru A.T.

    Published 2023
    Conference Paper
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  20. 20
    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar

    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

    Published 2015
    “…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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