Search Results - (( variable iteration method algorithm ) OR ( simulation optimization based algorithm ))
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…The proposed and the benchmark algorithms are tested for large-scale optimization problems which are associated with high-dimensional variability. …”
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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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Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…The Perturb and Observe (P&O) based maximum power point tracking (MPPT) was applied to the VS-MH and based on simulation. …”
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Proceedings -
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali
Published 2015“…This thesis is based on solving optimal control problems by using both direct and indirect methods. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…The thesis was set to three objectives as follows; to develop a new augmentation algorithm of Simplex method from the existed augmentation studies; to integrate the superiorities of the QSM and BLSA algorithms that can enhance computational performance; to compare the performance of the new augmentation algorithm with the conventional Simplex, QSM and BLSA in reducing iteration number. …”
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Partial Newton methods for a system of equations
Published 2013“…This is because it uses only one or two variables instead of all the search variables in each iteration.…”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The next method is simplex method. The simplex method is a conceptual model approach for analysing linear programming problems with any number of variables. …”
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Conference or Workshop Item -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…Broyden-Fletcher-Goldfarb-Shanno (BFGS) is one of a well-known Quasi-Newton update formula. This method is generally considered as the most efficient method among other variable metric methods for solving unconstrained optimization problems. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Research Book Profile -
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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