Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method

Li, An‐Da; He, Zhen; Zhang, Yang

doi:10.1016/j.compind.2016.05.008

Cited by 40 publications

(6 citation statements)

References 32 publications

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“…Because the results of the single weighting method are easily distorted, the AHP and entropy weight methods are used to combine the indicators, and the method of comprehensive weighting of indicators based on ideal points is used to solve the problem. Ideal point method (IPM) is a MCDM method that chooses the best compromise solution from many candidate solutions [59]. The objective and subjective weights are combined by IPM, which not only reflects the subjective experience of decision-makers, but also makes full use of the original data of indicators, so as to obtain more real and objective weights of indicators.…”

Section: Methods For Determining the Comprehensive Weight Of Indicatormentioning

confidence: 99%

Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model

Dong¹,

Wang²,

Liu³

et al. 2019

Sustainability

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The complex power system and trading environment in China has led to higher requirements for the efficient and stable operation of the electricity market. With the continuous advancement of power system reforms, regular evaluation of the operation of the market can help us grasp its status and trends, which is of great significance for ensuring its sustainable development. In order to effectively evaluate the current operational status of the electricity market, the concept of operation health degree of power market (OHDPM) is proposed to measure whether the operation is safe, efficient, and sustainable. This paper establishes an improved model framework based on the matter-element extension theory for evaluation. In order to effectively avoid information distortion and loss in the evaluation process, this paper combines the cloud model, matter element extension theory, ideal point method (IPM), and cloud entropy optimization algorithm to deal with this problem. The matter-element extension cloud model (MEECM) can clearly represent the characteristics of the object to be evaluated. IPM is used to determine the weight of the index. For the improved matter-element extension model, the traditional rules of “3En” and “50% relevance” are taken into account, and the method of solving the entropy is optimized. Then, for the correlation degree between the object to be evaluated and the graded normal cloud, the weight vector solved by the IPM is used to weigh the cloud correlation degree, which can give a reliable evaluation result. The health evaluation index system of power market operation includes 16 sub-indicators in five categories: supply side, demand side, coordinated operation, market security, and sustainable development. In the empirical analysis, the OHDPM situation in Y Province was evaluated in May 2019. The results prove that the OHDPM level is medium, and the importance and health level of each index are given. The reliability of the power system, transaction price stability, Lerner index, residual proportion of producers, and user satisfaction have a greater impact on the health status. Finally, in order to verify the validity and stability of the model, different methods are used to evaluate the evaluation objects, and the advantages of OHDPM evaluation based on the model framework proposed in this paper are proven.

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Section: Methods For Determining the Comprehensive Weight Of Indicatormentioning

confidence: 99%

Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model

Dong¹,

Wang²,

Liu³

et al. 2019

Sustainability

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show abstract

“…Namely, the smaller the gap is, the better the scheme is. As the set of ideal solutions of each objective, the ideal point can be subjectively determined by decision-makers or in accordance with the optimal value of a single objective [50]. erefore, by using the ideal point method, the evaluation function for member selection is obtained as follows:…”

Section: Construction Of a Fitness Functionmentioning

confidence: 99%

Member Selection for the Collaborative New Product Innovation Teams Integrating Individual and Collaborative Attributions

Zhang

Shan

et al. 2021

Complexity

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As the first stage of the formation of a collaborative new product innovation (CNPI) team, member selection is crucial for the effective operation of the CNPI team and the achievement of new product innovation goals. Considering comprehensively the individual and collaborative attributions, the individual knowledge competence, knowledge complementarity, and collaborative performance among candidates are chosen as the criteria to select CNPI team members in this paper. Moreover, using the fuzzy set and social network analysis method, the quantitative methods of the above criteria are proposed correspondingly. Then, by integrating the above criteria, a novel multiobjective decision model for member selection of the CNPI team is built from the view of individual and collaborative attributions. Since the proposed model is NP-hard, a double-population adaptive genetic algorithm is further developed to solve it. Finally, a real case is provided to illustrate the application and effectiveness of the proposed model and method in this paper.

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“…The hydraulic turbine governing system (HTGS) plays a predominant role in hydroelectric power plant to ensure safe, stable, economic, and efficient operation of the plant (Guo, Yang, & Teng, ; Li, He, & Zhang, ; Li & Zhou, ; Michelsen, Wilhelmsen, Zhao, & Åsen, ; Zhang, Chen, Xu, Wu, & Wang, ). The principle objective of HTGS is to regulate the hydraulic turbine‐generator set such as to generate the electrical power and frequency as per the dynamic demand of electric grid (Chen, Yuan, Ji, Wang, & Tian, ; Chen, Yuan, Yuan, Lu & Fernando, ).…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

Piraisoodi

Siluvairaj

Kappuva³

2018

Expert Systems

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The present paper proposes a novel multi‐objective robust fuzzy fractional order proportional–integral–derivative (PID) controller design for nonlinear hydraulic turbine governing system (HTGS) by using evolutionary computation techniques. The fuzzy fractional order PID (FOPID) controller takes closed loop error and its fractional derivative as inputs and performs fuzzy logic operations. Then, it produces the output through the fractional order integrator. The predominant advantages of the proposed controller are its capability to handle complex nonlinear processes like HTGS in heuristic manner, due to fuzzy incorporation and extending an additional flexibility in tuning the order of fractional derivative/integral terms to enhance the closed loop performance. The present work formulates the optimal tuning problem of fuzzy FOPID controller for HTGS as a multi‐objective one instead of a traditional single‐objective one towards satisfying the conflicting criteria such as less settling time and minimum damped oscillations simultaneously to ensure the improved dynamic performance of HTGS. The multi‐objective evolutionary computation techniques such as non‐dominated sorting genetic algorithm‐II (NSGA‐II) and modified NSGA‐II have been utilized to find the optimal input/output scaling factors of the proposed controller along with the order of fractional derivative/integral terms for HTGS system under no load and load turbulence conditions. The performance of the proposed fuzzy FOPID controller is compared with PID and FOPID controllers. The simulations have been conducted to test the tracking capability and robust performance of HTGS during dynamic set point changes for a wide range of operating conditions and model parameter variations, respectively. The proposed robust fuzzy FOPID controller has ensured better fitness value and better time domain specifications than the PID and FOPID controllers, during optimization towards satisfying the conflicting objectives such as less settling time and minimum damped oscillations simultaneously, due to its special inheritance of fuzzy and FOPID properties.

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Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method

Cited by 40 publications

References 32 publications

Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model

Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model

Member Selection for the Collaborative New Product Innovation Teams Integrating Individual and Collaborative Attributions

Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

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