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Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach
Published 1991“…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The pandemic has resulted in unpredictable customers’ purchasing patterns post-pandemic has rendered heuristic-based forecasting large forecast errors, which leads to poor decision-making. …”
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Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)...
Published 2013“…Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. …”
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Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias
Published 2019“…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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An experimental validation and optimisation tool path strategy for thin walled structure
Published 2011“…The target was to develop models which mimic the actual cutting process using the finite element method (FEM), to validate the developed tool path strategy algorithm with the actual machining process and to programme the developed algorithm into the software. …”
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Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems
Published 2024“…Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. …”
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Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…A user-friendly Graphical User Interface (GUI) is developed using Microsoft Visual Basic software to load and display the algorithm under test and display the result. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Two versions of the Jaya algorithm namely, the basic Jaya algorithm and novel quasi-oppositional Jaya (QOJaya) algorithm are proposed to solve different single objective OPF problems. …”
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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…MATLAB software is used to validate and evaluate the proposed model. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The proposed fuzzy adaptive teaching learning-based optimization algorithm uses three measures from the search space, namely, quality measure, diversification measure, and intensification measure. …”
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