Research On The IVHF-GRA Method For Competitive Evaluation Of Product Quality Design Schemes

The product quality design plan has a significant impact on product quality,and its competitive evaluation affects the design program's pros and cons.The competitive eval uation of product quality design can be divided into two parts: customer-driven product market competitiveness evaluation and product technology competitive evaluation led by experts.However,in the current research on the competitiveness evaluation of th e product quality design scheme,the risk appetite problem in the market competitiveness evaluation of the product quality design scheme is not considered,and the problem of the complex relationship between the indicators in the technical competitiveness evaluation of the product quality design scheme is not considered.Therefore,in order to solve these two problems,this paper applies the modified new Interval-Valued Hesitan t Fuzzy Relation Analysis method(IVHF-GRA)to the two parts of the assessment.The grey relation analysis method is an excellent multi-criteria decision-making method.It's calculation is simple,and the result is clear and intuitive,so it is widely used in many fields.In the product market competitiveness evaluation issues,due to customer-driven,there is a strong risk appetite in decision making.To deal with this issue,a grey prospective relation analysis that considering different risk preferences for customers when they face their own gains or losses was proposed;and consider ing that customers may appear regret in the face of other solution that may be better than the selected solution 's,grey regret relation analysis was proposed.Considering the issue of product technology competitiveness assessment,there may be negative co rrelation between indicators.Therefore,a gr ey compromise relation analysis which can deal with the negative correlation between indicators w as proposed.And considering the existence of a complex positive correlation between indicators,Grey likelihood r elation analysis which can deal with complex indicators was proposed.This article considers that decision makers(in this article mainly for customers and professional technical personnel)may not handle all aspects of knowledge when do some decision,and may occur different views between experts,and adopting anyone's idea may be inevitably neglected,so the grey relation analysis method and interval-valued hesitant fuzzy set theory were combined.For decision makers,it is easier to give a n interval-value than give an accurate value obviously,and the interval-valued hesitant fuzzy set can ta ke all the decision information into account,it can help the decision result reflect realistic experts' opinions.By combining the grey relational analysis method with the interval-valued hesitant fuzzy set,it can help enterprises get more scientific and reasonable evaluation results.When combining the interval-valued hesitant fuzzy set and grey relation an alysis method,the information measurements in the original grey relational analysis method have a little incompatibility.Although there are also corresponding interval-valued hesitant fuzzy measures such as interval-valued hesitant fuzzy distance measure and entropy measure,these formulas used to increased or de creased the number of interval-valued hesitant fuzzy elements in the interval-valued hesitant fuzzy set during the calculation,which reduced the accuracy of the result.In this paper,we proposed two new interval-valued hesitant fuzzy distance measures that do not change the number of elements of the interval-valued hesitant fuzzy sets,and two new kinds of interval-valued hesitant fuzzy entropy measures.Taking into account the importance of index denormalization,two new standardization formulas for inte rval-valued hesitant fuzzy set are also proposed.This article combined all of the above studies,using examples to illustrate the effectiveness of the proposed methods.