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lower optimization » level optimization (Expand Search), motor optimization (Expand Search), global optimization (Expand Search)
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lower optimization » level optimization (Expand Search), motor optimization (Expand Search), global optimization (Expand Search)
dog optimization » _ optimization (Expand Search), igdt optimization (Expand Search)
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems
Published 2023Subjects: “…Prairie dog optimization algorithm…”
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024Subjects: “…Teaching–learning-based optimization algorithm…”
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Optimization of PV Cleaning Practices: Comparison Between Performance-Based and Periodic-Based Approaches
Published 2020“…It is important to choose the right cleaning strategy (method and frequency) to maximize the electricity production and economic performance of the PV facility. An optimization algorithm was developed and tested for multiple PV panel configurations based in Dubai Water and Electricity Authority’s (DEWA) outdoor test facil ity (OTF) solar lab. …”
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Parallel physical optimization algorithms for allocating data to multicomputer nodes
Published 1994“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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Application of Red Deer Algorithm in Optimizing Complex functions
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…The second example involves a periodic beam with alternating thick and thin segments, modeled using WFE, where the objective is to minimize transmissibility over a lower frequency range. Five nature-inspired optimization algorithms: Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Particle Swarm Optimization (PSO) are compared. …”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The optimal planning of various energy resources is scheduled by a new optimization algorithm called Levy Flight and Chaos-assisted Artificial Rabbits Optimization (LFCARO), resulting in the lowest operational cost of this combined power system. …”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The optimal planning of various energy resources is scheduled by a new optimization algorithm called Levy Flight and Chaos-assisted Artificial Rabbits Optimization (LFCARO), resulting in the lowest operational cost of this combined power system. …”
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Cuckoo search for portfolio optimization. (c2014)
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The buffered work-pool approach for search-tree based optimization algorithms
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Natural optimization algorithms for optimal regression testing
Published 1997“…The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. …”
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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
Published 2023Subjects: “…Gradient-Based Optimizer…”
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A multi-objective planning approach for optimal DG allocation for droop based microgrids
Published 2021“…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …”
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The Hybrid Framework for Multi-objective Evolutionary Optimization Based On Harmony Search Algorithm
Published 2017“…In evolutionary multi-objective optimization, an evolutionary algorithm is invoked to solve an optimization problem involving concurrent optimization of multiple objective functions. …”
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