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  1. 1
    A generalized laser simulator algorithm for optimal path planning in constraints environment

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. …”
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  2. 2
    A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance

    A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance by Muhammad, Aisha, Ali, Mohammed A.H., Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Shanono, Ibrahim Haruna, Alzaid, Zaid, Alruban, Abdulrahman, Alabdan, Rana, Dutta, Ashit Kumar, Almotairi, Sultan

    Published 2022
    “…According to the results, the GLS algorithm outperformed the original laser simulator (LS) method in path and success rate. …”
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  3. 3
    Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion

    Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion by Ali, Mohammed A. H., Musa, Mailah, Jabbar, Waheb A., Moiduddin, Khaja, Ameen, Wadea, Alkhalefah, Hisham

    Published 2020
    “…A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. …”
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  4. 4
    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
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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  5. 5
    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
    “…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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  6. 6
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    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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  7. 7
    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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  8. 8
    A Collision Detection Algorithm For Virtual Robot-Centered Flexible Manufacturing Cell

    A Collision Detection Algorithm For Virtual Robot-Centered Flexible Manufacturing Cell by Arshad, Haslina

    Published 2008
    “…This thesis presents a collision detection algorithm for accurate simulation of a virtual flexible manufacturing cell. …”
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  9. 9
    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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  10. 10
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
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  11. 11
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Muhammad, Aisha, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Zubir, Mohd Nashrul, Faiz, Muhammad Khairi, Mohd Faizal, Erma Rahayu, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

    Published 2021
    “…This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. …”
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  12. 12
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Aisha, Muhammad, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Nashrul, Mohd Zubir, Muhammad Khairi Faiz, ., Erma Rahayu, Mohd Faizal, Abdulghafor, Rawad

    Published 2022
    “…This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. …”
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  13. 13
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Muhammad, Aisha, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Nashrul, Mohd Zubir, Muhammad Khairi, Faiz, Erma Rahayu, Mohd Faizal, Abdulghafor, Rawad

    Published 2022
    “…This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. …”
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  14. 14
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    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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  15. 15
    Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system

    Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
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  16. 16
    Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage

    Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

    Published 2023
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  17. 17
    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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  18. 18
    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed

    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

    Published 2017
    “…The results show that the proposed infeasible path detection method was efficient and detect 99 percent of the infeasible paths in the three industrial systems. …”
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  19. 19
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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  20. 20
    Robust multi-user detection based on hybrid grey wolf optimization

    Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

    Published 2020
    “…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
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