To identify interactions among evaluation criteria and describe their importance,a new identification method making use of a fuzzy measure is presented.The relative weight and interaction degree of every evaluation cr...To identify interactions among evaluation criteria and describe their importance,a new identification method making use of a fuzzy measure is presented.The relative weight and interaction degree of every evaluation criteria pair are obtained by using the diamond pairwise comparison method.Based on comparison results,the maximum eigenvector method of analytic hierarchy process （AHP）,the hierarchical clustering method,and the phi（s） transformation are utilized to generate values of the fuzzy measure for each subset of the evaluation criterion set.Overall evaluation on each supplier is aggregated by Choquet integral with respect to the fuzzy measure.Finally,an illustrative example demonstrates the practical feasibility and validity of the proposed method.展开更多
To be a worldwide competitor, enterprise needs to e va luate and select its supplier carefully. Generally, to evaluate a supplier, the evaluating effort is focused on the purchase price, delivery time, product quali t...To be a worldwide competitor, enterprise needs to e va luate and select its supplier carefully. Generally, to evaluate a supplier, the evaluating effort is focused on the purchase price, delivery time, product quali ty, etc. The vendors’ quality assurance is seldom considered. However, it reflec ts the ability that a vendor can provide high quality but low cost products cont inuously and stably. In this paper, with the study on evaluation of supplier’s q uality assurance system, a set of methods and indices to supplier’s quality assu rance evaluation is introduced. The indices construct an index system, which is based on the ISO9000 series standards. According to the problem’s character and the requirement of evaluation, all the evaluation indices are set off to three k inds: general index, functional index and protective index. And the evaluation m ethod combines quantitative analysis with qualitative analysis. Firstly, a sensi tive factor model is constructed to estimate the contribution of factors that ha ve key effect on synthetic evaluation in supplier’s quality system. Then, those suppliers having low evaluating value are rejected. Secondly, fuzzy logic is int roduced to evaluate other suppliers synthetically. The rest suppliers are compar able. So, supplier’s quality assurance system can be evaluated in quantity. Afte r unification works, the evaluated suppliers can be ranked. And the best vendor can be selected out intuitively.展开更多
基金Sponsored by the National Natural Science Foundation of China(7047106370771010)
文摘To identify interactions among evaluation criteria and describe their importance,a new identification method making use of a fuzzy measure is presented.The relative weight and interaction degree of every evaluation criteria pair are obtained by using the diamond pairwise comparison method.Based on comparison results,the maximum eigenvector method of analytic hierarchy process （AHP）,the hierarchical clustering method,and the phi（s） transformation are utilized to generate values of the fuzzy measure for each subset of the evaluation criterion set.Overall evaluation on each supplier is aggregated by Choquet integral with respect to the fuzzy measure.Finally,an illustrative example demonstrates the practical feasibility and validity of the proposed method.
文摘To be a worldwide competitor, enterprise needs to e va luate and select its supplier carefully. Generally, to evaluate a supplier, the evaluating effort is focused on the purchase price, delivery time, product quali ty, etc. The vendors’ quality assurance is seldom considered. However, it reflec ts the ability that a vendor can provide high quality but low cost products cont inuously and stably. In this paper, with the study on evaluation of supplier’s q uality assurance system, a set of methods and indices to supplier’s quality assu rance evaluation is introduced. The indices construct an index system, which is based on the ISO9000 series standards. According to the problem’s character and the requirement of evaluation, all the evaluation indices are set off to three k inds: general index, functional index and protective index. And the evaluation m ethod combines quantitative analysis with qualitative analysis. Firstly, a sensi tive factor model is constructed to estimate the contribution of factors that ha ve key effect on synthetic evaluation in supplier’s quality system. Then, those suppliers having low evaluating value are rejected. Secondly, fuzzy logic is int roduced to evaluate other suppliers synthetically. The rest suppliers are compar able. So, supplier’s quality assurance system can be evaluated in quantity. Afte r unification works, the evaluated suppliers can be ranked. And the best vendor can be selected out intuitively.
