Search Results - (( quality function based algorithm ) OR ( simulation optimization method algorithm ))
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1
Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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A hybrid MEP and AIS Algorithm for energy dispatch in power system
Published 2017“…Therefore, this paper introduces the new algorithm as an alternative method to provide the best solution in solving the single objective function of ED problems. …”
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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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4
Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…The PSSs design problem is transformed into an optimization problem which an eigenvalue-based objective function is developed and both the GA, PSO and the proposed FFA optimization methods are applied to search for the optimal control parameters of the PSSs that are connected to the multimachine in the power system. …”
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Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
Published 2016“…Conclusion: This study has explored the most effective heuristic method for solving TSPs based on the intended solution quality. …”
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HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets
Published 2018“…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)
Published 2011“…The implementations of the three methods to solve TSP show that the RTS algorithm provides a better solution in terms of minimizing the objective function while SA algorithm is less time consuming in solving problem with large number of cities.In conclusion, RTS is more effective in producing good quality solution and on the other hand, SA may be used to obtain instant results.…”
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9
Empowering Energy-Sustainable IoT Devices With Harvest Energy-Optimized Deep Neural Networks
Published 2024“…This paper applied the proposed Optimal Transmit Power and PS Ratio (OTPR) algorithm to maximize the EE for SWIPT based on the partial derivative of Lagrange dual decomposition methods. …”
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Reliable Fuzzy-Based Multi-Path Routing Protocol Based on Whale Optimization Algorithm to Improve QOS in 5G Networks for IOMT Applications
Published 2024“…The Whale Optimization Algorithm (WOA) enhances the routing protocol performance. …”
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Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation
Published 2024“…The optimized fuzzy controller shows superior performance in terms of transfer time, detection time, and harmonic reduction in comparison to those obtained without the PSO algorithm in all tested cases. � 1972-2012 IEEE.…”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
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Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices
Published 2021“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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14
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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15
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Results The method was tested with both simulated and real EEG data of 11 participants. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…An improved method that is based of the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. …”
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Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…To solve the model, an algorithm based on Simulated Annealing (SA) is developed in C/C++ namely SA1. …”
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Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
Published 2018“…The proposed work has been compared to GA-based technique, module modification technique and Simulated Annealing technique related to QR code readability, embedded logo visual quality and high embedded data capacity. …”
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Integration Of Travel Time Zone For Optimal Siting Of Emergency Facilities
Published 2008“…Fire stations in Jakarta Selatan were chosen for simulation. Two algorithms, Greedy Adding (Add) and Greedy Adding with Travel Time Evaluation (GAT), were applied to solve the optimization problem of the MSAP. …”
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