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  1. 1

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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    Thesis
  2. 2

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

    Published 2016
    “…In this paper, a modified Cuckoo searching algorithm is proposed to solve the multiple objective Green Logistics optimization problem. …”
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    Conference or Workshop Item
  3. 3

    A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham

    Published 2018
    “…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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    Article
  4. 4

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…Modification on the path by using neighborhood search significantly reduces the total length of the makespan. …”
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    Thesis
  5. 5

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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    Thesis
  6. 6

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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    Thesis
  7. 7

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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    Article
  8. 8

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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  9. 9

    Improved chemotaxis differential evolution optimization algorithm by Yıldız, Y. Emre, Altun, Oğuz, Topal, A. Osman

    Published 2015
    “…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
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  10. 10

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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    Article
  11. 11

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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    Article
  12. 12

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  13. 13

    Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

    Published 2018
    “…This thesis proposes a nature-inspired metaheuristic algorithm for global optimization. The proposed algorithm, which is called Ringed Seal Search (RSS), is inspired from the movement of the animal ringed seal. …”
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    Thesis
  14. 14

    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm by Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Nor Rul Hasma, Abdullah, Zainah, Md. Zain, Indra, Riyanto

    Published 2018
    “…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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    Book Chapter
  15. 15
  16. 16

    Cuckoo search algorithm for sizing optimization in grid-connected photovoltaic system: article / Wan Nur Liyana Wan Abd Rahman by Wan Abd Rahman, Wan Nur Liyana

    Published 2013
    “…Cuckoo Search algorithm is a new metaheuristic optimization algorithm that was recently developed by Yang and Deb in year 2009. …”
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    Article
  17. 17

    Cuckoo search algorithm for sizing optimization in grid-connected photovoltaic system / Wan Nur Liyana Wan Abd Rahman by Wan Abd Rahman, Wan Nur Liyana

    Published 2013
    “…Cuckoo Search algorithm is a new metaheuristic optimization algorithm that was recently developed by Yang and Deb in year 2009. …”
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    Thesis
  18. 18

    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

    Published 2017
    “…So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. …”
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    Thesis
  19. 19

    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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    Thesis
  20. 20

    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi... by Shukeri, Ahmad Zikri, Megat Sulzamzamendi, Puteri Qurratu Ain, Ibrahim, Suhaida

    Published 2024
    “…The result from this study is choosing FMRI algorithm using exact line search to get faster convergence rate which means that the algorithm achieves a high level of accuracy in fewer iterations compared to using other algorithms and inexact line search.…”
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    Student Project