Search Results - (( _ optimization ((method algorithm) OR (path algorithm)) ) OR ( using function means algorithm ))
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1
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. …”
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2
Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…This means A • algorithm only calculates and consider the next node m path that has the lowest value of G and F, plus searching the shortest route by using heuristic estimation in Manhattan method. …”
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3
Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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4
Optimization of multi-holes drilling toolpath using tiki-taka algorithm
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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5
Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks
Published 2012“…It is based on Ant Colony Optimization (ACO) meta heuristic, which is adopted to enhance the paths with the best-quality function. …”
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6
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…This study investigated the implementation and comparison between well known shortest path method which are Dijkstra’s algorithm, Bellman-Ford, and A* algorithm. …”
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8
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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9
MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM
Published 2019“…Path planning algorithm of Unmanned Aerial Vehicle (UAV) subject to find an optimal and collision free path in 3D space. …”
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Final Year Project Report / IMRAD -
10
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
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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12
The Implementation of Genetic Algorithm in Path Optimization
Published 2005“…Since 1800s when first mathematical problems related to TSP was treated, it became an interesting topic of optimization problem to be studied. In this project, TSP will be used to model and easy visualize the path optimization problem and Genetic Algorithm (GA) was chosen to be implemented in resolving the problem. …”
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13
Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The algorithm generates an integrated scheduling and detail paths route while optimizing makespan, AGV travel time, mean flow time and penalty cost due to jobs tardiness and delay as a result of conflict avoidance. …”
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14
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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15
Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques
Published 2014“…The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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16
Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks
Published 2024thesis::doctoral thesis -
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…Exploitation capability is the target hitting capability of an algorithm. Any algorithm with less exploitation capability or unbalanced capability missed many significant optima during optimization. …”
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18
New algorithm for autonomous dynamic path planning in real-time intelligent robot car
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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19
Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The comparison between euler's path and Bipartite graph Algorithm [14] will be made at the end this of this report to see which one give optimal chaining .…”
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20
Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm
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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