Results 11 to 20 of about 872,112 (308)
A Bayesian approach to constrained single- and multi-objective optimization [PDF]
, 2016 This article addresses the problem of derivative-free (single- or multi-objective) optimization subject to multiple inequality constraints. Both the objective and constraint functions are assumed to be smooth, non-linear and expensive to evaluate.
A Bayesian +7 more
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Lithosphere, 2022 Landslides have posed a huge threat to the ecological environment and human society all over the world. As the most conventional reinforcement method, anti-slide piles are widely used in the reinforcement of slopes. Currently, more and more attention has
Chao Xu +5 more
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A Simple Proposal for Including Designer Preferences in Multi-Objective Optimization Problems
Mathematics, 2021 Including designer preferences in every phase of the resolution of a multi-objective optimization problem is a fundamental issue to achieve a good quality in the final solution.
Xavier Blasco +4 more
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A constrained multi-objective surrogate-based optimization algorithm [PDF]
, 2014 Surrogate models or metamodels are widely used in the realm of engineering for design optimization to minimize the number of computationally expensive simulations.
Couckuyt, Ivo +3 more
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Algorithms, 2023 For multimodal multi-objective optimization problems (MMOPs), there are multiple equivalent Pareto optimal solutions in the decision space that are corresponding to the same objective value.
Jiajia Fan +3 more
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Scalarizing cost-effective multiobjective optimization algorithms made possible with kriging [PDF]
, 2007 The use of kriging in cost-effective single-objective optimization is well established, and a wide variety of different criteria now exist for selecting design vectors to evaluate in the search for the global minimum.
Hawe, G.I., Sykulski, J.K.
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IEEE Access, 2019 This paper presents a tri-level many-objective optimization (TLMaO) approach to provide a final solution for many-objective optimization problems (MaOPs).
J. H. Zheng +3 more
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MOBOpt — multi-objective Bayesian optimization
SoftwareX, 2020 This work presents a new software, programmed as a Python class, that implements a multi-objective Bayesian optimization algorithm. The proposed method is able to calculate the Pareto front approximation of optimization problems with fewer objective ...
Paulo Paneque Galuzio +3 more
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Friction stir welding parameter optimization using novel multi objective dragonfly algorithm
International Journal of Lightweight Materials and Manufacture, 2021 Friction stir welding (FSW) is a type of welding in which the joint is made in the solid phase using the heat generated through friction. FSW is used to produce welds with superior strength with low distortion. At present, the FSW technique is enormously
P. Pitchipoo +3 more
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Multi-Objective Big Data Optimization with jMetal and Spark [PDF]
, 2017 Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi ...
A Cabanas-Abascal +11 more
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