Search Results - (( based optimization method algorithm ) OR ( using systematic method algorithm ))
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1
Mathematical formulation of tabu search in combinatorial optimization
Published 2008“…CARP is known to be Non-deterministic Polynomialtime hard (NP-hard) where solutions are obtained through heuristic methods. Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. …”
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Monograph -
2
Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…First, this study examines the use of accuracy measure as a discriminator for building an optimized Prototype Selection (PS) algorithm. …”
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3
Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method
Published 2021“…In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. …”
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4
Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone
Published 2023“…Researchers use pheromone, which is a technique used by Ant Colony optimization algorithm, to enhance ABC and addressed several aspects of using a pheromone to enhance ABC. …”
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5
Systematic design of chemical reactors with multiple stages via multi-objective optimization approach
Published 2015“…By using reference-point based multi-objective evolutionary algorithm (R-NSGA-II), Pareto-optimal solutions are successfully generated within the region of user-specified reference points, thus facilitating in the selection of final optimal designs. …”
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6
OPTIMIZATION OF A CRUDE DISTILLATION UNIT USING PARAMETRIC DESIGN OF TAGUCHI AND RESPONSE SURFACE METHODS
Published 2014“…Variables with more than 90% contribution factors are selected and validated with the response surface method. A sequential quadratic programming (SQP) algorithm is then employed to optimize a profit function based onthereduced number of decision variables.…”
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7
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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8
Marine Predator Algorithm and Related Variants: A Systematic Review
Published 2025“…The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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9
Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method
Published 2022“…This review paper uses the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method to review the literature on LIRP systematically. …”
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Marine Predator Algorithm and Related Variants: A Systematic Review
Published 2025“…—The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. …”
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11
A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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12
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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13
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…To overcome such challenges, this study attempts to comprehend and improve the remote sensing technology for rooftop classification using the Worldview-3 (WV-3) image and object-based image analysis (OBIA) method. …”
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14
Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation
Published 2020“…Addressing the aforementioned issues, this research proposes the development and implementation of hybrid t-way strategy based Migrating Birds Optimization Algorithm (MBO) and Genetic Algorithm (GA) with elitism, termed Elitist Hybrid MBO-GA. …”
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15
Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…However, most scheduling methods lack a systematic approach to ensuring optimal power consumption reduction and comfort experienced by occupants. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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18
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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19
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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