Search Results - (( based optimization path algorithm ) OR ( using optimization strategy algorithm ))
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1
Simulated Kalman Filter algorithms for solving optimization problems
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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2
Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm
Published 2024“…Trajectory planning of robotic manipulators in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path planning, trajectory smoothing and optimization, and obstacle avoidance. This paper discusses different algorithms and finally proposes a fusion of the improved Dung Beetle Optimizer (IDBO) algorithm using chaotic mapping, sinusoidal random mutation, and nonlinear convergence strategies with the bidirectional Rapidly exploring Random Tree (RRT) algorithm to achieve manipulator trajectory planning and minimum jerk optimization trajectory. …”
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3
Path planning algorithm for a car like robot based on MILP method
Published 2013“…This approach is that the path optimization can be easily solved using the CPLEX optimization software with AMPL interface / MATLAB. …”
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4
A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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5
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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6
Improvement and application of particle swarm optimization algorithm
Published 2025“…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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7
QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)
Published 2008“…In this paper, a new algorithm, Intelligent agent AntNet based Routing Algorithm (IANRA) is proposed to enhance load balancing strategy in Wireless Networks (WNs). …”
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Using artificial intelligence search in solving the camera placement problem
Published 2022“…In general, artificial intelligence search strategies are extensively used in solving discrete optimization problems. …”
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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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10
An adaptive relay selection scheme for enhancing network stability in VANETs
Published 2020“…In this paper, we propose a new improvement to the mechanism of the Optimized Link State Routing Protocol(OLSR) protocol, named Cluster-based Adept Cooperative Algorithm (CACA), where each vehicle estimate a reliable low-overhead path using the cluster-based QoS algorithm. …”
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution
Published 2017“…Objectives: Our paper attempt to find an optimal route result for VRP by using K-Nearest Neighbor Algorithm (KNNA). …”
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12
Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation
Published 2017“…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
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13
Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis
Published 2017“…Therefore many research have been done to develop this type of computer game by using the Al techniques. In Dam Haji game, the goal is to find the optimal movement to make, so A* algorithm, which is a pathfinding algorithm is used. …”
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14
Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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15
Predetermined path of mobile data gathering in wireless sensor networks based on network layout
Published 2014“…There are two prevailing strategies used to collect data in sensor networks. …”
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Path Planning Optimization For Solar-Powered Perpetual Flight Across The World
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
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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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
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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19
Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks
Published 2009“…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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20
Articulated robots motion planning using foraging ant strategy
Published 2008“…However, the performance of this method is sub-optimal in terms of the number of configurations generated, length of path, amount of collision checking and computational time. …”
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