Search Results - (( using optimization max algorithm ) OR ( data evolution optimization algorithm ))
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…Two dynamic transmit antenna shuffling schemes, namely ‘Optimal’ and ‘Max STBC’, are proposed to enhance the V-BLAST/STBC transceiver scheme with LC-QR proposed in the first part. …”
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A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem
Published 2021“…The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches
Published 2015“…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses
Published 2019“…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system
Published 2023“…Algorithms; Costs; Evolutionary algorithms; Flow of water; Life cycle; Meteorology; Multiobjective optimization; Optimization; Probability; Pumping plants; Pumps; Solar power generation; Differential Evolution; Lifecycle costs; Meteorological data; Multi-objective differential evolution algorithms; Objective functions; Photovoltaic; Photovoltaic water pumping; Solar waters; Loss of load probability…”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…Kalman Filter and Bacterial Foraging algorithm helps in handling noise data and convergences faster respectively in the conventional Differential Evolution. …”
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Optimization of handover algorithms in 3GPP long term evolution system
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Proceeding Paper -
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Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization
Published 2013“…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
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An optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2017“…This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin
Published 2014“…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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Cross-layer design using multi-channel system in WiMAX mesh networks
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Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…Coordinated Multipoint (CoMP) in Long Term Evolution-Advanced (LTE- Advanced) improves the cell-edge data rates and the network spectral efficiency through base station coordination. …”
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A new minimum pheromone threshold strategy (MPTS) for max-min ant system
Published 2009“…Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. …”
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Efficient radio resource management algorithms for downlink long term evolution networks
Published 2018“…Optimal priority algorithm uses minimum data rate to guarantees resource allocation to users but increases the average delay and deteriorate the network performance. …”
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. …”
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