Search Results - (( java implementation path algorithm ) OR ( using meta study algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Comparative Study between Flower Pollination Algorithm and Cuckoo Search Algorithm for t-way Test Data Generation
Published 2018“…As a consequence, several meta-heuristic algorithms have been used as the basis of t-way strategies. …”
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Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
Published 2019“…Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…The first contribution entails a study on server consolidation, which employs the Locust Scheduling Meta-Heuristic Algorithm (LACE). …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…This study intends to show the superiority (time performance and quality of solution) of the proposed meta-heuristic Bat-BP algorithm over other more standard neural network training algorithms. …”
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch
Published 2016“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation
Published 2017“…Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. …”
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An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
Published 2023“…In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. …”
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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…In this paper, we study the advantages of fusing the Meta-Heuristic Bat Algorithm with Heuristic Optimization. …”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks
Published 2025“…Despite the growing use of MHAs, existing studies often focus on specific subsets of algorithms or narrow application domains, leaving a gap in understanding their comprehensive potential and comparative performance across diverse classification tasks. …”
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