Search Results - (( parameter optimization search algorithm ) OR ( evolution optimization approach algorithm ))
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. …”
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Differential evolution with improved sub-route reversal repair mechanism for multiobjective urban transit routing problem
Published 2018“…A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. …”
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Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach
Published 2024“…Drawing on a diverse dataset from a commercial building, encompassing vital input parameters such as Chilled Water Rate, Building Load, Cooling Water Temperature, Humidity, and Dew Point, the study conducts a comprehensive comparison of metaheuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Barnacles Mating Optimizer (BMO), Harmony Search Algorithm (HSA), Differential Evolution (DE), Ant Colony Optimization (ACO), and the latest RIME algorithm). …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2018“…GP is a meta-heuristic search and optimization technique based on natural evolution. …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2023“…GP is a meta-heuristic search and optimization technique based on natural evolution. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems
Published 2022“…In this paper, a new variant of Manta Ray Foraging Optimization (MRFO) algorithm is introduced to deal with real parameter constrained optimization problem. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. The results also show that the reduction of HOF through FuzAMP over conventional HHO algorithm is approximately 60%, 65%, and 66% at 3, 30, and 120 km/h, respectively, and over EWPHPO algorithm is approximately 30%, 46%, and 50% at 3, 30, and 120 km/h, respectively. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…Specifically, the downlink frequency domain scheduler will reconfigure the criteria priorities such that the EE is maximized as long as the QoS is guaranteed.On the other hand, the partial feedback algorithm will search for the threshold value that minimizes the uplink overhead given that the QoS is achieved at the downlink.Otherwise, optimizing QoS parameters will be targeted at the cost of other system parameters. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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Differentially expressed wound-response-related proteins from a major agarwood-producing tree, Aquilaria malaccensis Lam. identified via 2-D electrophoresis
Published 2018“…A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System
Published 2018“…Benchmarking has done by comparing the result obtained with the previous literature that implements Particle Swarm Optimization. The result indicates that the application of Gravitational Search Algorithm as parameters tuner for stereo matching’s parameters tuning is essentially on par with the Particle Swarm Optimization Algorithm.…”
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Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
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