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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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Global-best Brain Storm Optimization Algorithm
Published 2018“…Brain storm optimization (BSO) is a population-based metaheuristic algorithm that was recently developed to mimic the brainstorming process in humans. …”
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Island flower pollination algorithm for global optimization
Published 2019“…Comparing the results of IsFPA with those of state-of-the-art methods which are FPA, genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), multi-verse optimizer (MVO), island bat algorithm (iBA), and island harmony search (iHS), the comparison results show that the IsFPA is able to control the diversity and improves the outcomes where IsFPA is ranked first followed by FPA, iBA, iHS, GSA, MVO, GA, PSO, respectively, based on the Friedman test with Holm and Hochberg as post hoc statistical test.…”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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A Cooperative Co-evolutionary LSHADE Algorithm for Large-Scale Global Optimization
Published 2017“…In this paper, we propose the application of a Cooperative Co-evolutionary LSHADE (CCLSHADE) algorithm for Large-Scale Global Optimization (LSGO). …”
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A Hybrid Flower Pollination with p-Hill Climbing Algorithm for Global Optimization
Published 2021“…In this paper, the -hill climbing optimizer is hybridized with the flower pollination algorithm (FPA) as a local refinement operator for global optimization problems. …”
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Segmentation of thermographies from electronic systems by using the global-best brain storm optimization algorithm
Published 2023“…This paper proposes a combination of the minimum cross-entropy method and the Global-best brain storm optimization algorithm (GBSO), which improves the standard BSO to find the optimal solutions in complex search spaces. …”
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A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions
Published 2022“…The performance of seven swarm-based MPPT techniques is evaluated in this case study in terms of their settling time, convergence speed, overshoot, and efficiency under different levels of PSCs. The statistical analysis for 30 simulation runs shows that under heavier shading conditions, the grasshopper optimization algorithm (GOA) and salp swarm algorithm (SSA) outperform other swarm-based MPPT algorithms. …”
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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting
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doctoralThesis -
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Island artificial bee colony for global optimization
Published 2020“…The proposed iABC is evaluated using global optimization functions established by the IEEE-CEC 2015 which include 15 test functions with various dimensions and complexities (i.e., 10, 30, and 50). …”
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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
Published 2023“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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Particle swarm optimization algorithm: review and applications
Published 2024“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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Spark-based cooperative coevolution for large scale global optimization
Published 2023“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
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Spark-based cooperative coevolution for large scale global optimization
Published 2024“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
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GPU-based cooperative coevolution for large-scale global optimization
Published 2023“…The goal of researchers is to optimize the performance of algorithms in terms of both quality of solution and computational speed, seeing that large-scale optimization can be a computationally expensive process. …”
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