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  1. 1
    Simulated Kalman Filter algorithms for solving optimization problems

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

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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  2. 2
    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…When compared to the Ant Colony Optimization algorithm, Simulated Annealing and Genetic Algorithm, the results obtained from African Buffalo Optimization show that the algorithm works well and can be extended to solving problems like: path planning, scheduling, vehicle routing in addition to other constraint-driven problems.…”
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  3. 3
    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
    “…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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    Proceeding
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  4. 4
    Simulation of identifying shortest path walkway in library by using ant colony optimization

    Simulation of identifying shortest path walkway in library by using ant colony optimization by Chui Teng, Chan

    Published 2012
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  5. 5
    Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment

    Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment by Nurul Atikah Janis

    Published 2018
    “…Jump Point Search is one of the path finding algorithm with huge advantage of maintaining zero memory overhead as no preprocessing process involved. …”
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  6. 6
    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
    “…In the OSM-based scenarios, both algorithms yielded paths of identical length. …”
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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
    “…The whole constraint analyzer and the fitness function were combined with four SBTs (genetic algorithm, evolutionary algorithm, simulating annealing, and quantum genetic algorithm). …”
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  8. 8
    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
    “…The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. …”
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  9. 9
    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)

    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS) by Lim, Yai Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan

    Published 2011
    “…Traveling Salesman Problem (TSP) is a famous problem in combinatorial optimization. The objective of the TSP is to find the shortest path that reaches all the cities which are interconnected with each other by straight lines.The symmetric TSP is used and the distance between two cities is calculated by using Euclidean equation.In this study, three heuristic methods, namely simulated annealing (SA), tabu search (TS) and reactive tabu search (RTS) are used to solve TSP.SA is a generic probabilistic meta-algorithm for the global optimization problem and TS is a meta-heuristic search technique that guides a local search procedure to explore the solution space beyond local optimality. …”
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    Monograph
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  10. 10
    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
    “…The purpose of this study is to carry out a comparative evaluation study on Simulated Annealing (SA) and several variation of Tabu Search (TS).Materials and Method: This study considers four heuristic methods, i.e., Simulated Annealing (SA), conventional Tabu Search (TS), Improved Tabu Search (ITS) and modified Reactive Tabu Search (RTS) to solve symmetric TSPs.The algorithms were tested on five chosen benchmark problems. …”
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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
    Articulated robots motion planning using foraging ant strategy

    Articulated robots motion planning using foraging ant strategy by Mohamad, Mohd. Murtadha

    Published 2008
    “…This paper proposes a novel search technique, the F-Ant algorithm, in order to find a reliable path between the initial configuration and the goal configuration of the articulated robot. …”
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  13. 13
    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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  14. 14
    Design of A unmanned aerial vehicles assisted search and rescue collaboration architecture for emergency communication systems / Abdu Ahmed Saif Ahmed

    Design of A unmanned aerial vehicles assisted search and rescue collaboration architecture for emergency communication systems / Abdu Ahmed Saif Ahmed by Abdu Ahmed , Saif Ahmed

    Published 2022
    “…Simulation results indicate that the proposed algorithms can significantly reduce the outage probability and energy consumption. …”
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  15. 15
    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space

    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

    Published 2015
    “…A simulated robot in a simulated environment is used to test the algorithm that is to be developed. …”
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  16. 16
    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
    “…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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  17. 17
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Therefore, the IE algorithm exhibits significant potential for UAV path planning optimization…”
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  18. 18
    Route optimization using shortest path method / Muhamad Faisal Amin Shakri

    Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

    Published 2025
    “…Each algorithm was tested to compute the shortest path, with results indicating that while all algorithms arrive at the same optimal route, their efficiency differs. …”
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  19. 19
    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm

    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

    Published 2023
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  20. 20
    New algorithm for autonomous dynamic path planning in real-time intelligent robot car

    New algorithm for autonomous dynamic path planning in real-time intelligent robot car by Mohammed, Akeel Ahmed, Hassan, Mohd Khair, Aris, Ishak, Kamsani, Noor Ain

    Published 2017
    “…Different algorithms have been used to address this problem by considering the optimal path with minimum cost; however, these algorithms did not consider the execution time to find such path. …”
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