Search Results - (( developing unconstrained optimization algorithm ) OR ( java implication based algorithm ))
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Memoryless modified symmetric rank-one method for large-scale unconstrained optimization
Published 2009“…Computational results, for a test set consisting of 73 unconstrained optimization problems, show that the proposed algorithm is very encouraging. …”
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Hybrid DFP-CG method for solving unconstrained optimization problems
Published 2017“…The conjugate gradient (CG) method and quasi-Newton method are both well known method for solving unconstrained optimization method. In this paper, we proposed a new method by combining the search direction between conjugate gradient method and quasi-Newton method based on BFGS-CG method developed by Ibrahim et al. …”
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A three-term conjugate gradient method with nonmonotone line search for unconstrained optimization
Published 2016“…Numerical experiments carried out on benchmark test problems has clearly indicated the effectiveness of the developed algorithm in terms of efficiency and robustness.…”
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A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application
Published 2026“…The development of this new algorithm is based on the findings of recently introduced generalized RMIL CG technique. …”
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New Quasi-Newton Equation And Method Via Higher Order Tensor Models
Published 2010“…Moreover, a new limited memory QN method to solve large scale unconstrained optimization is developed based on the modified BFGS updated formula. …”
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An improvement of BFGS by applying n-th section method for solving unconstrained optimization / Nurul Atikah Mohamed Ramli
Published 2019“…Optimization is one of mathematics field that greatly developed when Quasi-newton method was presented to solve the unconstrained optimization problem. …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Monograph -
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The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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Quasi-Newton type method via weak secant equations for unconstrained optimization
Published 2021“…In this thesis, variants of quasi-Newton methods are developed for solving unconstrained optimization problems. …”
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Generalized Fibonacci search for optimization of unconstrained one-and two-dimensional unimodal functions
Published 2023“…Next, we execute the Bracketing Search to narrow the interval of uncertainty by developing a macro program in Microsoft Excel to optimize several one-dimensional benchmark functions. …”
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Product optimization of a fed-batch fermentation process
Published 2007“…Two strategies are considered. These are optimal control policy using direct-shooting algorithm and unconstrained Dynamic Matrix Control (DMC). …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Conclusively, the experimental and statistical evaluations performed in this study proved the capability of the developed NPO in solving real-world optimization problems.…”
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Formulation of model predictive control algorithm for nonlinear processes
Published 2004“…This is to determine if there is superiority of one over the other. An unconstrained MIMO DMC and nonlinear MPC (NNMPC) algorithms were developed using a step response model and two feedforward neural networks respectively. …”
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