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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…The Ant Colony Algorithm-Optimized Back Propagation Neural Network produced the highest accuracy for all parts of the skeleton where for femur was 89.44%, the humerus with 88.97% and tibia with 87.52% accuracy. …”
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Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…Furthermore, genetic algorithm (GA) has been used to optimize the FLCs performance. …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications
Published 2026“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…Recently, evolutionary algorithms (EA) are used to develop optimal operation rules for dam and reservoir water systems. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…This thesis will present the design, development and analysis of performance on a developed Double Stage Filter (DSF) algorithm and other existing stereo matching algorithms. …”
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Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System
Published 2016“…The dynamic parts of electro-hydraulic actuator(EHA) system are widely applied in the industrial field for the process that exposed to the motion control.In order to achieve accurate motion produced by these dynamic parts,an appropriate controller will be needed.However,the EHA system is well known to be nonlinear in nature.A great challenge is carried out in the EHA system modelling and the controller development due to its nonlinear characteristic and system complexity.An appropriate controller with proper controller parameters will be needed in order to maintain or enhance the performance of the utilized controller.This paper presents the optimization on the variables of sliding mode control (SMC) by using Particle Swarm Optimization (PSO) algorithm.The control scheme is established from the derived dynamic equation which stability is proven through Lyapunov theorem.From the obtained simulation results,it can be clearly inferred that the SMC controller variables tuning through PSO algorithm performed better compared with the conventional proportionalintegral-derivative (PID) controller.…”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
Published 2023“…The identification of optimized parameters for the ANN and fuzzy logic models is accomplished using innovative metaheuristic algorithms such as, Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO) and Imperialist Competitive Algorithm (ICA). …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…A technique for obtaining globally optimal schedules for the flow of crude is developed. …”
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Final Year Project -
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2009“…A technique for obtaining globally optimal schedules for the flow of crude is developed. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
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The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem
Published 2019“…The results are comparable with the results of advanced metaheuristic algorithms. Hence, suggesting that arbitrary exploration is practicable as an operator to solve optimization problems. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.…”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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