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  1. 1
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…It has been applied in many practical applications. For most of the cases of the shortest route finding, the Dijkstra's algorithm is known to be an optimal search algorithm. …”
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  2. 2
    Comparison of path planning in simulated robot

    Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

    Published 2020
    “…This is because each path planning algorithm has its own applicable domain, performance, advantages and disadvantages in various situations. …”
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  3. 3
    Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim

    Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim by Lukman Hakim, Mohamad Aliff Hakimi

    Published 2017
    “…This route-finding problem is one of the most important computer applications in the transportation industry. In network theory, it’s known as the shortest-path problem, and Dijkstra’s algorithm is usually used to solve it. …”
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  4. 4
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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  5. 5
    The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation

    The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2023
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    Proceeding
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  6. 6
    Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).

    Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2007
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  7. 7
    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
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  8. 8
    Reducing Iteration Using Candidate List

    Reducing Iteration Using Candidate List by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2008
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  9. 9
    Performance evaluation of heuristic methods in solving symmetric travelling salesman problems

    Performance evaluation of heuristic methods in solving symmetric travelling salesman problems by Lim, Yai-Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan, Baten, Md Azizul

    Published 2016
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  10. 10
    Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system

    Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar, Weria, Tang, Sai Hong, Mohamed Sahari, Khairul Salleh, Khaksar, Mansoor, Toressen, Jim

    Published 2019
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  11. 11
    Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system

    Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M., Torresen J.

    Published 2023
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  12. 12
    IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION

    IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION by SYED KHAIZURA, SYED HUSEIN KAMIL

    Published 2018
    “…In this study, we are looking at the performance of four graph-based path planning algorithms which is Breadth First Search, Depth First Search, Dijkstra and A*, when implemented in real world applications. …”
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  13. 13
    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution

    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

    Published 2017
    “…Approach: The approach has been presented based on two phases: firstly, the algorithms have been adapted to solve the research problem, where its procedure is different than the common algorithm. …”
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  14. 14
    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
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  15. 15
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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  16. 16
    Development of behavior-based reactive navigation system for mobile robot

    Development of behavior-based reactive navigation system for mobile robot by Mohd Hamami, Mohd Ghazali

    Published 2013
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  17. 17
    Implementation of autonomous vehicle navigation algorithms using event-driven programming

    Implementation of autonomous vehicle navigation algorithms using event-driven programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

    Published 2012
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  18. 18
    Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network

    Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network by Halim, Nurul Hamimi

    Published 2018
    “…However,the sink node position and size of data transmitted will not affect the performance of coverage area.This is because the coverage area value is fluctuated as the parameters value increases.Throughout the experiment conducted,sensor nodes deployed using Modified Harmony Search algorithm (MHS) gives better coverage area compared to other existing methods.The average coverage area percentage obtained by Modified Harmony Search is 63 %.The average coverage area percentage obtained by Modified Random is 48 % and the average coverage area percentage obtained by Harmony Search is 46 %.The highest coverage area recorded for Modified Harmony Search is 70 %.To enhance the energy efficiency,shortest path distance finder is added to each method.Throughout the research,Modified Harmony Search with shortest path distance finder gives optimum results.…”
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  19. 19
    Performance comparison of a and Dijkstra algorithms with bézier curve in 2D grid and OpenStreetMap scenarios

    Performance comparison of a and Dijkstra algorithms with bézier curve in 2D grid and OpenStreetMap scenarios by Yusuf, Zakariah, Mohamad, Sufian, Wan Ibrahim, Wan Suhaifiza

    Published 2025
    “…On the other hand, Dijkstra's algorithm, though robust and optimal, exhibited longer runtimes and produced paths with more turns due to its exhaustive search approach. …”
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  20. 20
    Robot path planning using family of SOR iterative methods with laplacian behaviour-based control

    Robot path planning using family of SOR iterative methods with laplacian behaviour-based control by Azali Saudi

    Published 2015
    “…In addition, the newly proposed LBBC overcomes the drawback of the existing GDS that face difficulty when handling complex environment. Finally, the path planning problem is solved by combining the fast iterative method with the robust path searching LBBC technique, so that the path planning algorithm is capable of handling large and complex environment.…”
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