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Scatter Search algorithm for Protein Structure Prediction
Published 2016“…In this paper, we present a Scatter Search (SS) algorithm for predicting 3D structures of proteins based on torsion angles representation. …”
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A new genetic algorithm approach for unit commitment
Published 1997“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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Evolutionary algorithms for VLSI multi-objective netlist partitioning
Published 2006“…In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). …”
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A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…The search space is too large to be explored by deterministic algorithms. In this paper, a Genetic Algorithm based algorithm for synthesis of MVL functions is proposed. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Published 2023“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The plant height of wild blueberry, field slope, and fruit zone readings were collected from each of the plots. For the purpose of predicting ground loss as a function of fruit zone, plant height, fruit production, slope, leaf loss, and blower damage, three ML models i.e., support vector regression (SVR), linear regression (LR), and random forest (RF)—were used. …”
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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem
Published 2020“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…We performed comprehensive experiments based on various functions, including 23 classical and IEEE CEC2017 problems. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…SA evolves a solution by minimizing an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…<p dir="ltr">Load balancing is a serious problem in cloud computing that makes it challenging to ensure the proper functioning of services contiguous to the Quality of Service, performance assessment, and compliance to the service contract as demanded from cloud service providers (CSP) to organizations. …”
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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
Published 2024“…Moreover, the proposed algorithm demonstrated excellent prediction accuracy with a mean absolute error (MAE) of <b>3.89</b> years, <b>3.64 </b>years, and <b>4.49</b> years for GM, WM, and CSF regions, confirming that changes in WM volume are significantly associated with normal brain aging. …”