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  1. 1
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…While quantitative technique is based on statistical concepts and requires large amount of data in order to formulate the mathematical models.This technique can be classified into projective and causal technique.The projective technique (or univariate modelling) just involve one variable while the causal technique (or econometric modelling) suitable for multi-variables.Since forecasting involves uncertainty, several methods need to be executed on one set of time series data in order to produce accurate forecast.Hence, usually in practice forecaster need to use several softwares to obtain the forecast values.If this practice can be transformed into algorithm (well-defined rules for solving a problem) and then the algorithm can be transformed into a computer program, less time will be needed to compute the forecast values where in business world time is money.In this study, we focused on algorithm development for univariate forecasting techniques only and will expand towards econometric modelling in the future.Two set of simulated data (yearly and non-yearly) and several univariate forecasting techniques (i.e. …”
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  2. 2
    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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  3. 3
    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
    “…Multi-objective swarm intelligence-based (MOSI-based) metaheuristics were proposed to solve multi-objective optimization problems (MOPs) with conflicting objectives. …”
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  4. 4
    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity

    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity by Ahmad Azwan, Abdul Razak

    Published 2019
    “…The second variant is known as Archived-based Multi-objective Spiral Dynamic Algorithm (MOSDA-A). …”
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  5. 5
    Review of Multi-Objective Swarm Intelligence Optimization Algorithms

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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  6. 6
    A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm

    A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm by Ahmmed, Mohammad Badal, Kamal Z., Zamli

    Published 2022
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  7. 7
    Multi-state PSO GSA for solving discrete combinatorial optimization problems

    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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  8. 8
    A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique

    A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

    Published 2022
    “…Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D) is one of the algorithms that utilize the concepts of decomposition and neighbourhood to solve multi-objective problems. …”
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  9. 9
    Solving multi-task optimization problems using the sine cosine algorithm

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

    Published 2022
    “…More precisely, our work investigates the adoption of partitioned population based on Sine Cosine algorithm for dealing with MTO problem. …”
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  10. 10
    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems

    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  11. 11
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Based on that result, it is concluded that multi-objective optimization problem can be solve using the applied method.…”
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    Undergraduates Project Papers
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  12. 12
    A novel multi-state gravitational search algorithm for discrete optimization problems

    A novel multi-state gravitational search algorithm for discrete optimization problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  13. 13
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…Particle Swarm Optimization (PSO) is a population-based metaheuristic that possesses many advantages compared to other metaheuristics in solving scheduling problems. …”
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  14. 14
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…The second algorithm is a multi-agent-based algorithm with synchronous update mechanism, named Multi-agent FIR optimizer (MAFIRO). …”
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  15. 15
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…The second algorithm is a multi-agent-based algorithm with synchronous update mechanism, named Multi-agent FIR optimizer (MAFIRO). …”
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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
    “…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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  17. 17
    Bats echolocation-inspired algorithms for global optimisation problems

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

    Published 2016
    “…Furthermore, a dual-particle swarm optimisation-modified adaptive bats sonar algorithm is proposed for solving multi objective optimisation problems. …”
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  18. 18
    An Improved Multi-State Particle Swarm Optimization for Discrete Optimization Problems

    An Improved Multi-State Particle Swarm Optimization for Discrete Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…Particle swarm optimization (PSO) has been successfully applied to solve various optimization problems. Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. …”
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  19. 19
    An improved multi-state particle swarm optimization for discrete combinatorial optimization problems

    An improved multi-state particle swarm optimization for discrete combinatorial optimization problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  20. 20
    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian

    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

    Published 2013
    “…Evolutionary multi-objective algorithms are considered as good candidate for solving multi-objective optimization problems and have been applied to variety of problems in different areas. …”
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