Search Results - (( using evolutionary path algorithm ) OR ( parallel optimization modified algorithm ))
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
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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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
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Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem
Published 2020“…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Review of the grey wolf optimization algorithm: variants and applications
Published 2023“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the scanning tasks need to be segregated and assigned for each scanner head, and path planning where the best combinatorial paths for each scanner are determined in order to minimize the total motion of scanning time. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025Article -
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Review of the grey wolf optimization algorithm: variants and applications
Published 2024“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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