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  1. 1
    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks

    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

    Published 2014
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  2. 2
    Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan

    Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan by Ruslan, Muhammad Hassan Firdaus

    Published 2017
    “…For the process module, Ant Colony Optimization (ACO) algorithm was used to find the shortest path. …”
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  3. 3
    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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  4. 4
    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
    “…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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  5. 5
    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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  6. 6
    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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  7. 7
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  8. 8
    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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  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
    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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  11. 11
    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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  12. 12
    Ant colony optimization (ACO) algorithm for CNC route problem

    Ant colony optimization (ACO) algorithm for CNC route problem by Wan Nur Farhanah , Wan Zakaria

    Published 2012
    “…The GUT will be display the shortest path that should be taken by user and give user authority to manipulate the coordinate based on the requirement.…”
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  13. 13
    An efficient virtual tour : a merging of path planning and optimization

    An efficient virtual tour : a merging of path planning and optimization by Abd Latiff, Muhammad Shafie, Hassan, Rohayanti

    Published 2004
    “…This paper describes the result of a research project aimed to integrate a path-planning optimization-algorithm and produce an efficient tour in a virtual environment. …”
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  14. 14
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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  15. 15
    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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  16. 16
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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