Search Results - (( swarm optimization methods algorithm ) OR ( using optimization path algorithm ))

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  1. 1

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
  2. 2

    Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm by Ahmad, Javed, Ab Wahab, Mohd Nadhir, Ramli, Ahmad, Misro, Md Yushalify, Ezza, Wan Zafira, Wan Hasan, Wan Zuha

    Published 2025
    “…The results reveal that our proposed method reduces the mobile robot's travel time by up to 69%, 67%, 72%, and 79% compared to these algorithms, while consistently achieving optimal path lengths. …”
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    Article
  3. 3

    Minimization of tool path length of drilling process using particle swarm optimization (PSO) by Abdullah, Haslina, Zaman, Nizam Nurehsan, Talib, Norfazillah, Lee, Woon Kiow, Saleh, Aslinda, Zakaria, Mohamad Shukri

    Published 2020
    “…For this study, the main purpose is to apply the Particle Swarm Optimization (PSO) algorithm for use in searching for the optimal tool routing path for in simulation of drilling process…”
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    Book Section
  4. 4

    Path planning for visually impaired people in an unfamiliar environment using particle swarm optimization by Yusof, T. S. T., Toha, Siti Fauziah, Md. Yusof, Hazlina

    Published 2015
    “…Here, in this paper, we propose a path planning with predetermined waypoints method using Particle Swarm Optimization (PSO) algorithm. …”
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    Article
  5. 5

    Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

    Published 2025
    “…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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    Article
  6. 6

    Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

    Published 2021
    “…This paper used a well-known metaheuristic optimization method, Particle Swarm Optimization (PSO) for solving AVRP models. …”
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    Conference or Workshop Item
  7. 7

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

    Published 2021
    “…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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    Proceedings
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  10. 10

    Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

    Published 2024
    “…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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    Final Year Project / Dissertation / Thesis
  11. 11

    A review on autonomous mobile robot path planning algorithms by Noraziah, Adzhar, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2020
    “…In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered.It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. …”
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    Article
  12. 12

    An optimal load shedding approach for transmission networks using Particle Swarm Optimization (PSO) technique / Mohd Farid Mohd Rawi by Mohd Rawi, Mohd Farid

    Published 2009
    “…This thesis presents an optimal load shedding approach for transmission networks using Particle Swarm Optimization (PSO). …”
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    Thesis
  13. 13

    A review on path planning and obstacle avoidance algorithms for autonomous mobile robots by Anis Naema Atiyah, Rafai, Noraziah, Adzhar, Nor Izzati, Jaini

    Published 2022
    “…Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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    Article
  14. 14

    An overview of mobile robot path planning by Noraziah, Adzhar, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2019
    “…The classical approaches such as cell decomposition, roadmap approach, artificial potential field (AFP), and heuristics approaches such as genetic algorithm, particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered in this study. …”
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    Conference or Workshop Item
  15. 15

    Optimization of multi-holes drilling toolpath using tiki-taka algorithm by Norazlina, Abdul Rahman

    Published 2024
    “…A computational experiment was conducted on 12 test problems across small, medium, and large problem categories using the TTA, then compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Crayfish Optimization Algorithm (COA), and Geometric Mean Optimizer (GMO). …”
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    Thesis
  16. 16

    DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization by Zulkifli, Md. Yusof, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi, Kamal, Khalil, Zuwairie, Ibrahim

    Published 2012
    “…Previously, direct-proportional length-based DNA computing which involved DNA sequences with different lengths has been implemented to solve the shortest path problem. In this study, particle swarm optimization (PSO) and population-based ant colony optimization (P-ACO) are employed to design DNA sequences with different lengths and the results obtained are compared. …”
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    Conference or Workshop Item
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    Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

    Published 2015
    “…This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). …”
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    Thesis
  19. 19

    Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

    Published 2018
    “…The proposed network reconfiguration also considered load profiles, DG output generation, DG types, and DG operating mode to decrease the total daily power loss. The chosen optimization techniques in this work include evolutionary programming (EP), particle swarm optimization (PSO), gravitational Search Algorithm (GSA), and firefly algorithm (FA). …”
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    Thesis
  20. 20

    Controller placement problem in the optimization of 5G based SDN and NFV architecture by Ibrahim, Abeer Abdalla Zakaria

    Published 2021
    “…If the control plane fails to improve system resilience quality, A reliable RAMCP is formulated as an optimal solution for fault tolerance. Furthermore, the approach is extended with a Particle Swarm Algorithm (PSO) and presented as a hybrid RASCP to validate the optimal location and number of controllers. …”
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    Thesis