Search Results - (( evolution optimization (problems OR problem) algorithm ) OR ( using function means algorithm ))

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  1. 1
    Broadening selection competitive constraint handling algorithm for faster convergence

    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 proposed algorithm has been evaluated using 24 benchmark functions. …”
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  2. 2
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…In this research, we applied SDAA to solve the constrained engineering problems and introduce an efficient data clustering algorithm which is hybrid of K-means and SDAA. …”
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  3. 3
    Crossover and mutation operators of real coded genetic algorithms for global optimization problems

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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  4. 4
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

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

    Published 2025
    “…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
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  5. 5
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

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

    Published 2025
    “…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
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  6. 6
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    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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  7. 7
    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses

    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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  8. 8
    A refined differential evolution algorithm for improving the performance of optimization process

    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
    Hybrid Optimization Genetic Algorithms (HOGA) with Interactive Evolution to Solve Constraint Optimization Problems for Production Systems .

    Hybrid Optimization Genetic Algorithms (HOGA) with Interactive Evolution to Solve Constraint Optimization Problems for Production Systems . by Vasant, Pandian

    Published 2007
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  10. 10
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…There are quite numbers of modern optimization algorithms proposed in the last two decades to solve optimization problems. …”
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  11. 11
    A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem

    A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem by Asaad Shakir, Hameed, Mohd Aboobaider, Burhanuddin, Mutar, Modhi Lafta, Ngo, Hea Choon

    Published 2020
    “…The Combinatorial Optimization Problem (COPs) is one of the branches of applied mathematics and computer sciences, which is accompanied by many problems such as Facility Layout Problem (FLP), Vehicle Routing Problem (VRP), etc. …”
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  12. 12
    Sub-route reversal repair mechanism and differential evolution for urban transit network design problem

    Sub-route reversal repair mechanism and differential evolution for urban transit network design problem by Tarajo, Buba Ahmed

    Published 2017
    “…This thesis considers the urban transit network design problem (UTNDP) focusing on the implementation of population-based metaheuristic approaches, specifically on differential evolution (DE) and particle swarm optimization (PSO). …”
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  13. 13
    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model by Ayda, Emdadian, Ponnambalam, S. G., Kanagaraj, G.

    Published 2018
    “…In this paper, five variants of Differential Evolution (DE) algorithms are proposed to solve the multi-echelon supply chain network optimization problem. …”
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  14. 14
    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem

    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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  15. 15
    Exploring dynamic self-adaptive populations in differential evolution

    Exploring dynamic self-adaptive populations in differential evolution by Teo, Jason Tze Wi

    Published 2006
    “…Although the Differential Evolution (DE) algorithm has been shown to be a simple yet powerful evolutionary algorithm for optimizing continuous functions, users are still faced with the problem of preliminary testing and hand-tuning of the evolutionary parameters prior to commencing the actual optimization process. …”
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  16. 16
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

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

    Published 2017
    “…Optimal PMU Placement (OPP) problem as the combinatorial optimization problem has been formulated to determine the minimum PMU location in the power system. …”
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  17. 17
    Improved chemotaxis differential evolution optimization algorithm

    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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  18. 18
    Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization

    Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization by Qin, Feng, AZLAN, MOHD ZAIN, KAI-QING, ZHOU, Norfadzlan, Yusup, DIDIK DWI, PRASETYA, ROZITA, ABDUL JALIL, ZAHEERA, ZAINAL ABIDIN, MAHADI, BAHARI, YUSRI, KAMIN, MAZLINA, ABDUL MAJID

    Published 2025
    “…Harmony search algorithm (HSA) is extensively utilized in engineering optimization. …”
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  19. 19
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  20. 20
    Differential evolution with improved sub-route reversal repair mechanism for multiobjective urban transit routing problem

    Differential evolution with improved sub-route reversal repair mechanism for multiobjective urban transit routing problem by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2018
    “…A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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