Simulation and particle swarm optimization
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In line with that research trend, this paper proposes a hybrid algorithm combining particle swarm optimization with the simulated annealing technique (PSO-SA) to optimize the length of intervals to improve forecasting accuracies.
19p vimurdoch 18-09-2023 7 4 Download
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This study suggests a new metaheuristic algorithm for global optimization, based on parallel hybridizing the swarm optimization (PSO) and Gravitational search algorithm (GSA). Subgroups of the population are formed by dividing the swarm’s community. Communication between the subsets can be developed by adding strategies for the mutation. Twenty-three benchmark functions are used to test its performance to verify the feasibility of the proposed algorithm.
11p linyanjun_2408 21-04-2022 19 3 Download
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Metaheuristic search algorithms are used to develop new protocols for optimal intravenous insulin infusion rate recommendations in scenarios involving hospital in-patients with Type 1 Diabetes. Two metaheuristic search algorithms are used, namely, Particle Swarm Optimization and Covariance Matrix Adaption Evolution Strategy.
28p redemption 20-12-2021 14 0 Download
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This paper focusses on the computational aspects of infectious disease models and applies commonly available graphics processing units (GPUs) for the simulation of these models. However, fully utilizing the resources of both CPUs and GPUs requires a carefully balanced heterogeneous approach.
11p viconnecticut2711 28-10-2020 15 0 Download
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Protein-ligand docking has emerged as a particularly important tool in drug design and development, and flexible ligand docking is a widely used method for docking simulations. Many docking software packages can simulate flexible ligand docking, and among them, Autodock is widely used.
20p vicolorado2711 22-10-2020 8 0 Download
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Results show how different settings of kanban influence the performance of the assembly line feeding system. The biggest novelty item is certainly the recognition of the trade-off between kanban size and number of kanban and the importance of investigating its behaviour during the design of the system.
22p toritori 11-05-2020 19 1 Download
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An optimization-simulation strategy has been applied by coupling a commercial process simulator (Aspen HYSYS ) with a programming tool (MATLAB ) to produce a precise steady state simulationbased optimization of a whole green-field saturated gas plant as a real case study. The plant has more than 100-components and comprises interacting three-phase fractionation towers, pumps, compressors and exchangers. The literature predominantly uses this coupling to optimize individual units at small scales, while paying more attention to optimizing discrete design decisions.
13p partimesinhvien 08-05-2020 19 0 Download
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In this paper a nonlinear quarter car suspension–seat–driver model was implemented for optimum design. A nonlinear quarter car model comprising of quadratic tyre stiffness and cubic stiffness in suspension spring, frame, and seat cushion with 4 degrees of freedom (DoF) driver model was presented for optimization and analysis.
17p kequaidan1 16-11-2019 15 0 Download
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In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables.
10p kequaidan1 16-11-2019 38 0 Download
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In view of the fact that to get the analytic solutions of the inverse kinematics of robots must meet special conditions, this paper used a general solution, simulated annealing particle swarm optimization algorithm, to obtain the optimization of inverse kinematics without any special conditions.
4p praishy2 27-02-2019 42 3 Download
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In this study, we consider a variant of the Bilevel Uncapacitated Facility Location Problem (BLUFLP), in which the clients choose suppliers based on their own preferences. We propose and compare three metaheuristic approaches for solving this problem: Particle Swarm Optimization (PSO), Simulated Annealing (SA), and a combination of Reduced and Basic Variable Neighborhood Search Method (VNS).
18p vinguyentuongdanh 19-12-2018 16 0 Download