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  1. 1

    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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  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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  3. 3

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

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. 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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  4. 4

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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  5. 5

    Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

    Published 2015
    “…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). …”
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  6. 6

    A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

    Published 2020
    “…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
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  7. 7

    A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

    Published 2016
    “…To find out the answer for this question, four well-known and most commonly-used algorithms are tested. Particle swarm optimization (PSO), Differential Evolution (DE), Genetic Algorithms (GA), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are tested in three different setups of experiments. …”
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  8. 8

    Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

    Published 2022
    “…MRFO is a recently new introduced algorithm that consists of strategy of foraging adopted by Manta Ray while Gradient-based Mutation (GbM) is a feasibility-and solution repair strategy adopted from ϵ-Matrix-Adaptation Evolution Strategy (ϵ-MAES). …”
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  9. 9

    Application of manta ray foraging optimization with gradient-based mutation (cMRFO) for solving power system problems by Ahmad Azwan, Abd Razak, Ahmad Nor Kasruddin, Nasir

    Published 2023
    “…In this paper, the Manta Ray Foraging Optimization (MRFO) algorithm is applied to solve real parameter constrained optimization problems, using the Gradient-based Mutation MRFO (cMRFO) variant. …”
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  10. 10

    Optimizing crystal size distribution based on different cooling strategies in batch crystallization process by Siti Zubaidah, Adnan, Noor Asma Fazli, Abdul Samad

    Published 2024
    “…Based on the simulation results, optimization IV, which maximizes CSD, performs best with a large mean crystal size of 490 µm. …”
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  11. 11

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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  12. 12

    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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    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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  15. 15

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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  16. 16

    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Rayner Alfred, Kim, On Chin

    Published 2013
    “…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

    Published 2015
    “…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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  19. 19

    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Jason, Teo, Kim, On Chin, Alfred, Rayner

    Published 2013
    “…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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