Results 11 to 20 of about 106,374 (297)
Fast multi-swarm optimization for dynamic optimization problems [PDF]
2008 Fourth International Conference on Natural Computation, 2008 This article is posted here with permission of IEEE - Copyright @ 2008 IEEEIn the real world, many applications are non-stationary optimization problems. This requires that the optimization algorithms need to not only find the global optimal solution but
Li, C, Yang, S
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Parameters Optimization of Tuned Mass Damper Using Fast Multi Swarm Optimization
Jurnal Teknik Sipil, 2019 Tuned mass damper (TMD) has been used for vibration controller of building, especially for high rise building. TMD is one of passive device for reducing response of the structure which subjected to dynamic external disturbance such as wind, or ...
Richard Frans, Yoyong Arfiadi
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Multi-Guide Set-Based Particle Swarm Optimization for Multi-Objective Portfolio Optimization
Algorithms, 2023 Portfolio optimization is a multi-objective optimization problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio optimization requires a trade-off coefficient to be specified in order to balance ...
Kyle Erwin, Andries Engelbrecht
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Multitasking Multi-Swarm Optimization [PDF]
2019 IEEE Congress on Evolutionary Computation (CEC), 2019 Multi-task optimization (MTO) is a newly emerging research area in the field of optimization, studying on how to solve multiple optimization problems at the same time so that the processes of solving different but relevant problems could help each other via knowledge transfer to improve the overall performance of solving all problems. Evolutionary MTO (
Hui Song +3 more
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Multi-Swarm Algorithm for Extreme Learning Machine Optimization
Sensors, 2022 There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which makes it suitable for integration within products that require models taking rapid decisions. Nevertheless,
Nebojsa Bacanin +5 more
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An Adaptive Multi-Swarm Optimizer for Dynamic Optimization Problems [PDF]
Evolutionary Computation, 2014 The multipopulation method has been widely used to solve dynamic optimization problems (DOPs) with the aim of maintaining multiple populations on different peaks to locate and track multiple changing optima simultaneously. However, to make this approach effective for solving DOPs, two challenging issues need to be addressed.
Changhe, Li +2 more
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EURASIP Journal on Wireless Communications and Networking, 2020 In order to improve the adaptive management ability of virtual machine placement in cloud computing, an adaptive management and multi-objective optimization method for virtual machine placement in cloud computing is proposed based on particle swarm ...
Shuxiang Li, Xianbing Pan
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Multi-objective optimization of a redundantly actuated parallel robot mechanism for special machining [PDF]
Mechanical Sciences, 2022 In order to improve the accuracy and efficiency of special machining for a complex surface, a 2RPU-2SPR (where R, P, U, and S stand for revolute, prismatic, universal, and spherical joints, respectively) over-constrained redundantly actuated parallel ...
H. Zhang +7 more
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Multi-layer optimization algorithm
Journal of Algorithms & Computational Technology, 2022 The optimization of experimental results has repeatedly posed major challenges for scientist and engineers. In this work, a systematic multi-layer optimization scheme is proposed in conjunction with particle swarm optimization algorithm to locate a ...
M Abdalla, J Yamin, E Al-Khawaldeh
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Multi-swarm multi-objective optimization based on a hybrid strategy
Alexandria Engineering Journal, 2018 Multi-objective optimization is a very competitive issue that emerges naturally in most real world problems. It is concerned with the optimization of conflicting objectives in multi-objective problems.
Shery Sedarous +2 more
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