Interval multiobjective optimization of structures based on radial basis function, interval analysis, and NSGA-II

Cheng, Jin; Duan, Guifang; Liu, Zhenyu; Li, Yong; Feng, Ying; Chen, Xiao-hai

doi:10.1631/jzus.a1300311

Cited by 27 publications

(12 citation statements)

References 38 publications

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“…The analytic hierarchy process method was used to calculate the coefficient. Its judgment matrix could be estimated by [30] (15) where α ij is the ratio of importance between two optimization objectives.…”

Section: Optimized Resultsmentioning

confidence: 99%

“…A unified method was developed for the uncertainty quantification of dis brake squeal for two fuzzy-interval cases, while the unified uncertain response was computed with the aid of the combination of level-cut strategy, Taylor series expansion, subinterval analysis and Monte Carlo simulation [14]. Both probability distribution function and membership function need a lot of data, however, the engineering problems have finite data [15]. The interval method could make up for the above shortcomings [16].…”

Section: Introductionmentioning

confidence: 99%

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Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

Liu

Xiao

et al. 2019

Applied Sciences

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With respect to heavy carrying tasks and uneven road surface in open pit mine, the mechanical performances of electric wheel dump truck frame regarded as the main bearing component are extremely important for its safe operation. For the problem of insufficient strength and stiffness, an interval multi-objectives optimization design method based on blind number theory is presented in this paper, taking into account uncertain factors caused by manufacturing process. The allowable interval strength of welding material and permissible interval bending and torsional stiffness are obtained by means of experiments and simulations, using the blind number theory. Based on Latin hypercube sampling technique, the strength and stiffness of frame under different conditions is estimated. It shows that in the case of braking interference between interval strength and interval dynamic stress appears. Strength and stiffness are considered as optimization objectives, while the thicknesses of top longitudinal beam, stiffener, lateral longitudinal beam and hanging ear in the frame are deeded as design variables, and Young’s modulus and Poisson’s ratio are taken as uncertain variables. The optimized results show that the stress and deformation of the frame due to dynamic loading decreased. This result enables to formulate the following sentence: the mechanical performance of frame is improved.

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Section: Optimized Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

Liu

Xiao

et al. 2019

Applied Sciences

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“…To achieve high punching precision, good operational reliability and low manufacturing cost for a high-speed press, we previously investigated the constrained interval multi-objective optimization of the slider mechanism based on interval analysis and NSGA-II [27], the robust optimization of the slider mechanism based on normalized violation degree of interval constraint [28] and the reliability-based design optimization of the upper beam [29], in which the uncertainties in the material properties were described as interval parameters and the manufacturing costs were evaluated by the weights of key components. It is worth noting that the decision optimization problem investigated here still exists after locating a group of Pareto optimal solutions by NSGA-II.…”

Section: Hmadm Modeling Of the Optimization Problemmentioning

confidence: 99%

Structural Optimization of a High-Speed Press Considering Multi-Source Uncertainties Based on a New Heterogeneous TOPSIS

et al. 2018

Self Cite

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Abstract:In order to achieve high punching precision, good operational reliability and low manufacturing cost, the structural optimization of a high-speed press in the presence of a set of available alternatives comprises a heterogeneous multiple-attribute decision-making (HMADM) problem involving deviation, fixation, cost and benefit attributes that can be described in various mathematical forms due to the existence of multi-source uncertainties. Such a HMADM problem cannot be easily resolved by existing methods. To overcome this difficulty, a new heterogeneous technique for order preference by similarity to an ideal solution (HTOPSIS) is proposed. A new approach to normalization of heterogeneous attributes is proposed by integrating the possibility degree method, relative preference relation and the attribute transformation technique. Expressions for determining positive and negative ideal solutions corresponding to heterogeneous attributes are also developed. Finally, alternative structural configurations are ranked according to their relative closeness coefficients, and the optimal structural configuration can be determined. The validity and effectiveness of the proposed HTOPSIS are demonstrated by a numerical example. The proposed HTOPSIS can also be applied to structural optimization of other complex equipment, because there is no prerequisite of independency among various attributes for its application.

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“…Firstly, the interval objective function is transformed by the interval relation, then the interval constraint is transformed based on the interval possibility degree [6]. According to a definition of the interval ranking relation "   …”

Section: The Transformation Of Uncertain Optimizationmentioning

confidence: 99%

A parallel optimization method for product configuration and supplier selection based on interval

Zheng

Zhang

2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. In the process of design and manufacturing, product configuration is an important way of product development, and supplier selection is an essential component of supply chain management. To reduce the risk of procurement and maximize the profits of enterprises, this study proposes to combine the product configuration and supplier selection, and express the multiple uncertainties as interval numbers. An integrated optimization model of interval product configuration and supplier selection was established, and NSGA-II was put forward to locate the Pareto-optimal solutions to the interval multiobjective optimization model. IntroductionProduct configuration is an effective way to achieve rapid product development. In the environment of mass customization, the product configuration design based on product family, with high efficiency and low cost of mass production to achieve the design and production of personalized products, so as to enhance the enterprise's rapid response ability and market competition ability. After the product configuration scheme is determined, according to the enterprise business strategy making production plan and outsourcing parts procurement plan, there is a selection of the best suppliers for parts. Rational selection of suppliers can help companies reduce costs and increase management flexibility, improve the core competitiveness of enterprises, and long-term cooperation with high quality suppliers, so as to effectively reduce the risk of procurement and maximize the profits of enterprises.At present, domestic and foreign scholars have done a lot of research on product configuration and supplier selection, considering the integration of product configuration and supplier selection is still rare. Jiang and other research on inventory driven product configuration optimization problem, the establishment of multi-objective optimization model and genetic algorithm [1]; Ostrosi and others regard the product configuration problem as the mapping process between multiple fuzzy models, and optimize the effective configuration scheme by the self-defined fuzzy configuration syntax to get the optimal solution [2]; considering the uncertain information of the new components, Liu et al. have established a fuzzy multi-objective configuration optimization model, and use mixed integer nonlinear programming algorithm to solve [3]; Yeh and others in the supplier selection criteria framework to add green guidelines, and the establishment of a multi-objective mixed integer nonlinear programming model, the use of multi-objective genetic algorithm for optimal solution [4]; Luo and other people to establish a product family design and supplier selection of a unified optimization model to maximize

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Interval multiobjective optimization of structures based on radial basis function, interval analysis, and NSGA-II

Cited by 27 publications

References 38 publications

Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

Structural Optimization of a High-Speed Press Considering Multi-Source Uncertainties Based on a New Heterogeneous TOPSIS

A parallel optimization method for product configuration and supplier selection based on interval

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