Results 11 to 20 of about 848,743 (149)
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
doaj +1 more source
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
doaj +1 more source
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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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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Functional Brain Imaging with Multi-Objective Multi-Modal Evolutionary Optimization [PDF]
, 2006 Functional brain imaging is a source of spatio-temporal data mining problems. A new framework hybridizing multi-objective and multi-modal optimization is proposed to formalize these data mining problems, and addressed through Evolutionary Computation (EC)
A. Hyvarinen +14 more
core +4 more sources
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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Hybrid behavioural-based multi-objective space trajectory optimization [PDF]
, 2009 In this chapter we present a hybridization of a stochastic based search approach for multi-objective optimization with a deterministic domain decomposition of the solution space.
Vasile, Massimiliano
core +1 more source
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
doaj +1 more source
Integrated Energy Multi-Objective Operation Optimization [PDF]
E3S Web of Conferences, 2020 The Integrated Energy System (IES) offers a new approach to the energy dilemma. It introduces demand-side response into the Regional Integrated Energy System (RIES) and proposes an operational optimization model considering Integrated Demand Side ...
Liu Zhao +7 more
doaj +1 more source
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
core +5 more sources