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  1. 1
    Modelling of multi-robot system for search and rescue

    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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  2. 2
    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
    “…The second approach is the modification of heuristic computation using original A* and modified Bresenham. Bresenham Line Algorithm is a line generation algorithm using integer arithmetic where the points (x1, y1) and (x2, y2) are assumed not equal and integer valued. …”
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  3. 3
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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  4. 4
    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
    “…Most metaheuristic algorithms are designed for continuous optimization problem. …”
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  5. 5
    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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  6. 6
    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
    “…Results: The analysis of computational results showed that the modified RTS algorithm provided a better solution quality in terms of minimizing the objective function of TSPs, while the SA algorithm was useful for obtaining instant solutions for TSPs with a large number of cities. …”
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  7. 7
    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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  8. 8
    Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network

    Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network by Al-Kharasani, Nori Mohammed Abdulkarem

    Published 2020
    “…The proposed Quality of Path QoP metric is incorporated into the modified relay selection algorithm, which improves the efficiency of relay selection mechanism to find optimal path with high link quality. …”
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  9. 9
    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm

    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

    Published 2015
    “…Employing a multi-robot system and path planning with spanning tree algorithm is a strategy for speeding up sensor node deployment. …”
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  10. 10
    Cut-off solar charge controller as an alternative towards system efficiency optimization

    Cut-off solar charge controller as an alternative towards system efficiency optimization by Sabry, Ahmad H., Almassri, Ahmed M., Wan Hasan, Wan Zuha, Mohd Radzi, Mohd Amran, Ab Kadir, Mohd Zainal Abidin, Shafie, Suhaidi

    Published 2014
    “…A Simulink Matlab simulator is attempted in the simulation phase of this research. …”
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  11. 11
    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system

    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

    Published 2021
    “…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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  12. 12
    SNR-Based OLSR Routing Protocol for Wireless Mesh Networks

    SNR-Based OLSR Routing Protocol for Wireless Mesh Networks by Elobaid, Mohamed Elshaikh

    Published 2009
    “…Unfortunately the routing protocols used such as AODV and Dynamic source routing (DSR) are hop count-based; where the routing algorithm uses the number of nodes to determine the optimum path to the destination. …”
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  13. 13
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…The motion planning problem poses the question of how a robot can move from an initial to a final position. Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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  14. 14
    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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  15. 15
    MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM

    MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM by Teng, Chu Yao

    Published 2019
    “…The existing methods aim for planning optimal path of drone flight. In this report, a variant of A*, Theta* algorithm is proposed to find the optimal path within a grid-based environment. …”
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  16. 16
    Multi-robot path planning based on the improved nutcracker optimization algorithm and the dynamic window approach

    Multi-robot path planning based on the improved nutcracker optimization algorithm and the dynamic window approach by Zhao, Jiangrong, Ding, Hongwei, Zhu, Yuanjing, Yang, Zhijun, Hu, Peng, Wang, Zongshan

    Published 2024
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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
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  18. 18
    A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System

    A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Mohammed, M.A

    Published 2021
    “…Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. …”
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  19. 19
    Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm

    Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm by Kasim Hawari, Mohd Zarifitri

    Published 2023
    “…The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle.…”
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  20. 20
    Mobile robot path planning using hybrid genetic algorithm and traversability vectors method

    Mobile robot path planning using hybrid genetic algorithm and traversability vectors method by Loo, C.K., Rajeswari, M., Wong, E.K., RaoTask, M.V.C.

    Published 2004
    “…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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