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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
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  2. 2

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

    Published 2020
    “…The mean closure performance of the BSCCH algorithm is compared against seven selected state-of-the-art algorithms, namely Differential Evolution with Adaptive Trial Vector Generation Strategy and Cluster-replacement-based Feasibility Rule (CACDE), Improved Teaching Learning Based Optimization (ITLBO), Modified Global Best Artificial Bee Colony (MGABC), Stochastic Ranking Differential Evolution (SRDE), Novel Differential Evolution (NDE), Partical Swarm Optimization for solving engineering problems-a new constraint handling mechanism (CVI-PSO) and Ensemble of Constraint Handling Techniques (ECHT). …”
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    Article
  3. 3

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
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    Article
  4. 4

    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

    Published 2019
    “…Simulation results show that, at the high-level inverter, the proposed algorithm can easily find the feasible solutions, however, GA, PSO, bee algorithm (BA), and differential evolution (DE) face the difficulty due to less exploration capability. …”
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    Thesis
  5. 5

    Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization by Goh, Khang Wen

    Published 2019
    “…The probabilistic/metaheuristic approaches are methods based on probability, genetic and evolution as its metaheuristic function for the guidance when solving the global optimization problem, and their accuracy of the solution obtained are not guaranteed. …”
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    Thesis
  6. 6

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…Bees Algorithm is one of the optimization algorithms inspired from the natural foraging ways of the honey bees of finding the best solution. …”
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    Thesis
  7. 7

    Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

    Published 2019
    “…To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.…”
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    Article
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    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…The Bees Algorithm is used in this study to find the optimum solution for stepped-cone pulley design and found better results compared to other optimization algorithms.…”
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    Book Chapter
  11. 11

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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    Article
  12. 12

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

    Published 2011
    “…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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    Conference or Workshop Item
  13. 13

    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
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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    Article
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    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
    “…A modified artificial bee optimization is proposed in this study. The algorithm is based on the colony behavior of certain bee species to achieve optimal solution in the bounded environment. …”
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    Article
  16. 16

    An improved bees algorithm local search mechanism for numerical dataset by Al-Dawoodi, Aras Ghazi Mohammed

    Published 2015
    “…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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    Thesis
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    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  19. 19

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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    Article
  20. 20

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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    Conference or Workshop Item