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模糊AHP與非加法型模糊積分法於工程承包廠商評選之研究

Fuzzy AHP and Non-Additive Fuzzy Integral Methods for Evaluation and Selection of Construction Project Contractor

摘要


營造廠在評選其單項工程承包商時有許多評估準則諸如成本、品質等,傳統的評估方法通常為:求得各準則之權重後,對各替選方案依每個準則評分,最後予以加總與排名。但在實際評估過程中,不論是權重或評分,其資訊都是具模糊性的,故本文以模糊AHP法來處理此種多準則、多層級、資訊具模糊性的問題。而在現實生活中,評估準則間是具影響性的,即考慮單個準則的重要性與數個準則一起考慮的重要性不具相加性,故本文應用λ-模糊測度與非加法型模糊積分法代替模糊AHP法中原有的加總方法。但傳統模糊積分法之權重及評分是一組確定值,在加總前需將模糊權重與模糊評點作非模糊化(Defuzzification)的工作。為不使實際資訊流失,本文提出權重及評點為模糊數的模糊積分法,其總評估值仍為一組模糊數,最後將模糊總評估值作排名,選出最佳承包商。本文首先介紹模糊AHP法、λ-模糊測度、非加法型模糊積分法之三種概念及方法,並提出權重及評分為模糊數的模糊積分法,再以一實例驗證,比較非加法型模糊積分法與傳統加權法之差異及其實用性,發現模糊積分法更能突顯各準則平均發展的健全承包商,較符合實際需要。最後討論λ值不同時對排名可能發生的影響,發現λ越大、因素間相乘性越高時,各替選方案其因素滿意度(即其評分)差異性越能顯現。

並列摘要


The evaluation and selection of contraction works, in terms of contractor for every single category, has been made in many evaluation criteria such as cost, quality and so forth, and the conventional manner of evaluation would be: once the weight for each of the criterion would be given, which will be then summed up and ranked. However, during the processes of evaluation in practice, whether it is either weight or rate score its information would be of fuzzy problem. While on our life, there exists mutual influence among each of the evaluation criteria as well as that of several criteria is not summative, it is why this paper has chosen to employ λ-fuzzy measure and non-additive fuzzy integral methods to replace the original aggregate summation method found in fuzzy AHP. Since the weight and rate score of conventional fuzzy integral method are of a set of definite values, it is necessary that the fuzzy weight and fuzzy rate score have to be conducted of defuzzification before the summation. In order to prevent the information in aggregate will be ranked so as to find out the best contractor. This paper will, at first, introduce fuzzy AHP, λ-measure, the concept and method of as non-additive fuzzy integral. Then, an example will be employed to substantiate so as to show the difference between non-additive fuzzy integral can better come up with such contractor with accommodate the realty even more. At the end, possible impacts on ranking will greater the λ value and the multiplication will be higher among elements, then the difference in terms of its satisfaction (rate score) among each of the alternatives will be more pronounced.

參考文獻


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