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  1. 1
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). …”
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  2. 2
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). …”
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  3. 3
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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  4. 4
    Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture

    Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture by Ibrahim, Abeer Abdalla Zakaria, Hashim, Fazirulhisyam, Noordin, Nor Kamariah, Sali, Aduwati, Navaie, Keivan, Fadul, Saber Mohammed Elnour

    Published 2021
    “…A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. …”
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  5. 5
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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  6. 6
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  7. 7
    Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.]

    Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.] by Heru Triharjanto, Robertus

    Published 2016
    “…It is also find that due to full acces level, the self-made simulator as used in the research has good potential to be used in the optimization case with search algorithm.…”
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  8. 8
    A calibration framework for swarming ASVs' system design

    A calibration framework for swarming ASVs' system design by Zainal Abidin, Zulkifli

    Published 2012
    “…Swimming pool provides as a controlled calibration framework for the proposed swarming algorithm. …”
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  9. 9
    Basic firefly algorithm for document clustering

    Basic firefly algorithm for document clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents.The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. …”
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  10. 10
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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  11. 11
    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm

    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm by Wang, Wei, Liu, Yao

    Published 2016
    “…Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. …”
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  12. 12
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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  13. 13
    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems

    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  14. 14
    Mathematical formulation of tabu search in combinatorial optimization

    Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

    Published 2008
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    Monograph
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  15. 15
    Particle swarm optimization (PSO) for CNC route problem

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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  16. 16
    Particle Swarm Optimization algorithm for facial emotion detection

    Particle Swarm Optimization algorithm for facial emotion detection by Ghandi, B.M., Nagarajan, R., Hazry, Desa, Prof. Madya Dr.

    Published 2010
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  17. 17
    Tackling the berth allocation problem via harmony search algorithm

    Tackling the berth allocation problem via harmony search algorithm by Ahmed, Bilal, Hamdan, Hazlina, Muhammed, Abdullah, Husin, Nor Azura

    Published 2024
    “…Harmony Search Algorithm (HSA) is one of the recent population-based optimization methods which inspired by modern-nature. …”
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  18. 18
    The design and applications of the african buffalo algorithm for general optimization problems

    The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

    Published 2017
    “…Optimization, basically, is the economics of science. …”
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  19. 19
    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian

    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian by Tey, Siew Kian

    Published 2009
    “…Power system state estimation is the heart of data processing activities of modern electric utility energy control center. By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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  20. 20
    Local search manoeuvres recruitment in the bees algorithm

    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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