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Optimal Management of Mobile Energy Generation and Storage Systems
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Optimizing Energy Consumption of Cloud Computing IaaS
Published 2017Subjects: Get full text
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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On Indefinite Quadratic Optimization over the Intersection of Balls and Linear Constraints
Published 2022“…<p>In this paper, we study the minimization of an indefinite quadratic function over the intersection of balls and linear inequality constraints (QOBL). Using the hyperplanes induced by the intersection of each pair of balls, we show that the optimal solution of QOBL can be found by solving several extended trust-region subproblems (e-TRS). …”
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995)
Published 1995Get full text
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Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg...
Published 2023“…The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…On the other hand, the optimization of the problem is implemented using several evolutionary-based metaheuristic algorithms. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…All these developed algorithms have some merits and also demerits. Particle swarm optimization (PSO), firefly algorithm, ant colony optimization (ACO), and bat algorithm (BA) have gained much popularity and they have successfully tackled various test suites of benchmark functions and real-world problems. …”
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Minimum UAV fog servers with maximum IoT devices association using genetic algorithms
Published 2021“…We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. …”
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A new family of multi-step quasi-Newton algorithms for unconstrained optimization
Published 1999“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…Second, a hybrid genetic-whale optimization algorithm was proposed to optimize ontology learning from Arabic text. …”
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