Results 11 to 20 of about 21,806 (260)
Multiobjective Bayesian optimization for online accelerator tuning
Physical Review Accelerators and Beams, 2021 Particle accelerators require constant tuning during operation to meet beam quality, total charge and particle energy requirements for use in a wide variety of physics, chemistry and biology experiments.
Ryan Roussel, Adi Hanuka, Auralee Edelen
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IEEE Access, 2022 As the working efficiency and life span of the shovel plate of a roadheader directly influence its performance, optimization of the shovel-plate parameters is crucial. For optimizing the shovel-plate parameters, the variations in the loading capacity and
Qiang Li, Songyong Liu, Mengdi Gao
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A Fusion Multiobjective Empire Split Algorithm
Journal of Control Science and Engineering, 2020 In the last two decades, swarm intelligence optimization algorithms have been widely studied and applied to multiobjective optimization problems. In multiobjective optimization, reproduction operations and the balance of convergence and diversity are two
Liang Liang
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09041 Summary – Hybrid and Robust Approaches to Multiobjective Optimization [PDF]
, 2009 The seminar “Hybrid and Robust Approaches to Multiobjective Optimization” was a sequel to two previous Dagstuhl seminars (04461 in 2004 and 06501 in 2006). The main idea of this seminar series has been to bring together two contemporary fields related to
Zitzler, Eckart +3 more
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Stochastic Fractal Based Multiobjective Fruit Fly Optimization
International Journal of Applied Mathematics and Computer Science, 2017 The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective ...
Zuo Cili +3 more
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A mono surrogate for multiobjective optimization [PDF]
Proceedings of the 12th annual conference on Genetic and evolutionary computation, 2010 Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective Optimization Algorithm (EMOA) in lieu of the actual objectives, without modifying the underlying EMOA; or to filter out points that the models predict to be uninteresting.
Loshchilov, Ilya +2 more
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Abstract and Applied Analysis, 2014 A calmness condition for a general multiobjective optimization problem with equilibrium constraints is proposed. Some exact penalization properties for two classes of multiobjective penalty problems are established and shown to be equivalent to the ...
Shengkun Zhu, Shengjie Li
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Orthogonality in multiobjective optimization
Applied Mathematics Letters, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alejandro Balbás +2 more
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A method for generating a well-distributed Pareto set in nonlinear multiobjective optimization [PDF]
, 2009 A method is presented for generating a well-distributed Pareto set in nonlinear multiobjective optimization. The approach shares conceptual similarity with the Physical Programming-based method, the Normal-Boundary Intersection and the Normal ...
Utyuzhnikov, S.V.; id_orcid +7 more
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International Journal of Distributed Sensor Networks, 2015 Based on multiobjective particle swarm optimization, a localization algorithm named multiobjective particle swarm optimization localization algorithm (MOPSOLA) is proposed to solve the multiobjective optimization localization issues in wireless sensor ...
Ziwen Sun +3 more
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