Evolutionary multi-objective optimization assisted by metamodels, kernel PCA and multi-criteria decision making techniques with applications in aerodynamics

Kapsoulis, Dimitrios; Τσιάκας, Κωνσταντίνος; Trompoukis, Xenofon; Asouti, Varvara; Giannakoglou, Kyriakos C.

doi:10.1016/j.asoc.2017.11.046

Cited by 26 publications

(26 citation statements)

References 16 publications

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“…In some aerodynamic designs, the application of PCA is mainly on the data processing, e.g., classifier. Some examples can be seen in reduced-order models for simulations balancing computation cost and flowfield accuracy in numerous fields [22,[53][54][55][56].…”

Section: Principal Component Analysis As Data Manipulatormentioning

confidence: 99%

“…The solution proposed in this paper is done via Principal Component Analysis (PCA). PCA is used to strengthen preprocessing of data to improve manipulation efficiency [21,22], dimension reduction [23], and in the sample selection of initialization [24], etc. The methods for data manipulation have been utilized in aerodynamic designs, but mostly in design space than in objective space.…”

Section: Introductionmentioning

confidence: 99%

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The Objective Space and the Formulation of Design Requirement in Natural Laminar Flow Optimization

Wang

Sun

2020

Applied Sciences

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Design requirement is as important in aerodynamic design as in other industries because it sets up the objective for the samples in design space to approach. Natural Laminar Flow (NLF) optimization belongs to the type of aerodynamic design problems featured by the combination of distinct aerodynamic performance, where the design requirement is often formulated in form of summation of laminar-related performance and pressure drag performance with different weight assignment according to different perspectives. However, the formulations are rather experience-oriented and are decided non-quantitatively. Inspired by data manipulation approaches in design space (spanned by design variables of geometrical representation parameters) in many aerodynamic designs, this paper proposes new formulations of design requirement in NLF optimization via consideration of objective space (projection of design space through aerodynamics) and shows the impact of the corresponding formulation of design requirement to the result of NLF optimization in cases of transonic airfoil and aero engine compressor blade design from two perspectives: Pareto front convergence and improving effect of accessory performance. The paper uses Principal Component Analysis (PCA) to obtain the eigenvectors of objective space to extract the intrinsic information about specific problem. The method is realized in two cases with satisfactory result.

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Section: Principal Component Analysis As Data Manipulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Objective Space and the Formulation of Design Requirement in Natural Laminar Flow Optimization

Wang

Sun

2020

Applied Sciences

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“…Although all three algorithms are able to solve the reduction problem, the emphasis is somewhat different [8,15]. For example, the RS theory mainly focuses on the attribute reduction problem [23,28] and shows much potential in the multilabel learning [29,36], while the PCA is usually applied to the dimension reduction problem in the machine learning [9,16] and multi-objective optimization (MOO) [18,20]. What's more, the RS theory reduces attributes based on the partition of equivalence relation, which can be accomplished through the evaluation metric [30,31], like mutual information and information entropy [10,38].…”

Section: Literature Review 21 Index System Reduction Algorithmsmentioning

confidence: 99%

Index System Reduction Method Based on the Index Similarity

Gao

2019

Teh. vjesn.

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Multi-attribute decision making (MADM) always suffers from the result inconsistency and computational complexity problem, due to numbers of redundant and relational attributes (indexes) of the initial evaluation index system. Therefore, this paper studies the index system (IS) reduction problem through selecting the most representative indicator from each index subsystem after the IS structure partition. First, we propose and demonstrate the Index Subsystem Judgement theorem to improve the efficiency of the classic system structure partition algorithm. Second, an algorithm of index system reduction based on the index similarity (ISRS) is put forward. The ISRS is able to reduce the index quantity while still keeping the index meaning. Third, we define the direction loss rate to measure the evaluation ability loss of the IS during reduction. The algorithm is tested for a synthetic dataset to compare the proposed ISRS with different index reduction algorithms, followed by an extensive experimentation with a real-world financial dataset. Experiment results illustrate that our proposed method is able to obtain more accessible and available reduction results in practice.

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“…The weighted summation method is used widely in practical engineering for MDOP because of its comparability. [21][22][23][24][25][26] It should be noted that the value of objective satisfaction degree can be represented by weight coefficients.…”

Section: Introductionmentioning

confidence: 99%

An enhanced genetic algorithm–based multi-objective design optimization strategy

Yuan

Wang

2018

Advances in Mechanical Engineering

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In this study, an enhanced genetic algorithm is proposed to solve multi-objective design and optimization problems in practical engineering. In the given approach, designers choose available design results from the given samples first. These samples are reordered according to their mutual relationships. After that, designers choose an exact ratio of conformity as available field. Furthermore, more weight information can be obtained through finding the minimum value of the norm of unconformity and satisfactory samples. These samples can be used to reflect the preference chosen for Pareto design solutions. A structure design problem of speed increaser used in wind turbine generator systems is solved to show the application of the given design strategy.

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Evolutionary multi-objective optimization assisted by metamodels, kernel PCA and multi-criteria decision making techniques with applications in aerodynamics

Cited by 26 publications

References 16 publications

The Objective Space and the Formulation of Design Requirement in Natural Laminar Flow Optimization

The Objective Space and the Formulation of Design Requirement in Natural Laminar Flow Optimization

Index System Reduction Method Based on the Index Similarity

An enhanced genetic algorithm–based multi-objective design optimization strategy

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