高倩 李國棟
摘 要: 為有效地幫助企業(yè)快速找到合適的供應商合作伙伴,采用直覺模糊集、評分函數(shù)等方法對TOPSIS評估法進行優(yōu)化,并以此為基礎建立了一種供應商選擇模型。
首先,采集和評估供應商的產(chǎn)品質(zhì)量、產(chǎn)品價格、產(chǎn)品交貨的可靠性、供應位置、財務情況、庫存水平、勞資關系、發(fā)展能力和技術能力等相關信息,由專家給出主觀評估信息,匯總為綜合屬性值;然后,通過直覺模糊熵確定各評估指標的權重;最后,綜合考慮供應商選擇決策過程中的多個目標和標準,應用改進TOPSIS法的對供應商進行分類選擇。結果顯示,基于改進TOPSIS法的供應商選擇模型能夠較準確地反映出各供應商的真實水平和對企業(yè)的潛在價值,可以有效地解決不確定條件下對供應商的選擇問題,提高了供應商選擇結果的可靠性。改進后的模型簡便易行,具有良好的穩(wěn)定性,對于合理制定企業(yè)供應商選擇標準以及進一步優(yōu)化決策模型具有一定的借鑒意義。
關鍵詞: 決策理論;TOPSIS法;選擇;供應鏈;供應商
中圖分類號: F202? ?文獻標識碼:? A
doi:? 10.7535/hbgykj.2020yx06005
Research on supplier selection model based on
improved TOPSIS method
GAO Qian, LI Guodong
(School of Chinese Law and Economic Management, Shengli College China University of Petroleum, Dongying,Shandong? 257000, China)
Abstract:
In order to help enterprises find suitable supplier partners effectively in a short time, the TOPSIS evaluation method was optimized by utilizing intuitionistic fuzzy sets and scoring functions, based on this, a supplier selection model was established. Firstly, the product information of suppliers such as quality, product price, delivery reliability, supply location, financial situation, inventory level, labor relation, development ability and technical ability of suppliers was collected and evaluated. After that, the subjective evaluation information was given by experts, and comprehensive attribute values were obtained. Then, the weight of each evaluation index was determined by intuitionistic fuzzy entropy. Finally, taking multiple objectives and criteria into consideration in the process of supplier selection, the improved TOPSIS method was applied to classify and? select? suppliers. The results show that the supplier selection model based on improved TOPSIS method can accurately reflect the true level and potential value of each supplier for enterprises. It can effectively solve the problem of supplier selection under uncertain conditions, and improve the reliability of supplier selection results. With merits of easier operation and better stability, the improved model provides significant reference for making reasonable supplier selection standards and further optimizing the decision-making model.
Keywords:
decision theory; TOPSIS method; selection; supply chain; supplier
國內(nèi)外學者對供應商選擇的研究主要集中在2個方面:一方面是供應商選擇決策過程的方式和模型;另一方面是供應商的選擇標準。針對決策過程的方式和模型角度,曹一哲等? [1] 指出,供應商的選擇本質(zhì)上是一個決策過程,其目的是將潛在供應商的初始集合盡可能縮減,以便在最后決策時能夠從極少的幾個備選單位中挑選出最佳供應商。先從現(xiàn)有的供應商庫中選擇或者尋找新的供應商,再根據(jù)當前情況對供應商的多個定量和定性指標進行評估,從而確定最終供應商。趙國軍? [2] 認為由于部分無相關數(shù)據(jù)作為參考,大多數(shù)情況下的決策過程都存在不確定性,同時,多位決策者對定性和定量指標的評估具有主觀性,一定程度上影響了評估結果的準確性。
1) 穩(wěn)定性 使用改進模型對供應商進行排序,不斷微調(diào),觀察模型數(shù)據(jù)在多次指標權重不同情境下的變化情況,發(fā)現(xiàn)改進TOPSIS模型對指標權重的調(diào)整是相對穩(wěn)定的。因此,生產(chǎn)企業(yè)可以依據(jù)改進模型對供應商進行篩選。
2) 真實性 利用改進TOPSIS模型對企業(yè)的產(chǎn)品質(zhì)量、產(chǎn)品采購價格、產(chǎn)品交貨的可靠性、供應位置、財務情況、庫存水平、勞資關系、發(fā)展能力和技術能力等方面進行評估,能夠反映出供應商的實際水平和潛在價值。
3) 高效性 改進模型基于選擇決策的多角度指標,將直覺模糊集和評分函數(shù)融入傳統(tǒng)的TOPSIS決策評價方法,對供應商的產(chǎn)品質(zhì)量等9項指標進行測算,并對供應商進行分類選擇,最終篩選出能夠真正體現(xiàn)實際潛力及客觀水平的供應商。因此,改進模型能夠幫助企業(yè)準確、迅速地挑選出合適的供應商。
改進的供應商選擇模型的評價指標采用的是單一的評估類型值(即直覺模糊集數(shù)據(jù)類型),具有一定的局限性。為了提高模型的適用性,建議今后應嘗試采用多種評估類型值(例如語言形式評估值、主觀評估值、客觀評估值等)對評價對象作出多維度評價,進一步提高模型的準確性。
參考文獻/References:
[1]? 曹一哲,楊玉中.基于熵值修正BWM的煤炭企業(yè)綠色供應商選擇評價模型及應用[J].河南理工大學學報(社會科學版), 2020, 21 (4): 34-40.
CAO Yizhe, YANG Yuzhong. An entropy modification BWM-based evaluation model of green supplier selection for coal? enterprises? and its application[J]. Journal of Henan Polytechnic University (Social Sciences), 2020, 21 (4): 34-40.
[2]? 趙國軍.基于三角模糊集和MCDM的企業(yè)供應鏈管理績效評估[J]. 財會月刊, 2016(30):80-83.
[3]? 劉麗霞. 建設材料分類及供應商選擇研究[D]. 大連: 大連理工大學, 2016.
LIU Lixia. Research on Construction Material Segmentation and Supplier Selection [D].Dalian: Dalian University of Technology, 2016.
[4]? 史金朋. 改進TOPSIS法的裝備可靠性評估方法[J].計算機測量與控制,2017,25(8):300-303.
SHI Jinpeng. A reliability evaluation method of equipment on improved TOPSIS[J]. Computer Measurement and Control, 2017,25 (8): 300-303.
[5]? GOVINDAN K, RAJENDRAN S, SARKIS J, et al. Multi-criteria decision making approaches for green supplier evaluation and selection: A literature review[J].Journal of Cleaner Production, 2015, 98(1):66-83.
[6]? KAR A K. A hybrid group decision support system for supplier selection using analytic hierarchy process fuzzy set theory and neural network[J].Journal of Computational Science, 2015,6:23-33.
[7]? 趙婷婷.應急物流發(fā)展的現(xiàn)狀與戰(zhàn)略[J].遼寧工業(yè)大學學報(社會科學版),2020,22(2):38-40.
[8]? 傅少川,黃亞卿.考慮風險規(guī)避的生鮮混合雙渠道供應鏈協(xié)調(diào)研究[J].武漢理工大學學報(信息與管理工程版),2020,42(2):115-122.
FU Shaochuan, HUANG Yaqing. Coordination of fresh and mixed dual-channel supply chain with risk aversion[J]. Journal of Wuhan University of Technology (Information and Management Engineering), 2020, 42(2): 115-122.
[9]? 白楊敏,李炎.生態(tài)系統(tǒng)視角下的物流產(chǎn)業(yè)集群創(chuàng)新體系研究——以天津市為例[J].物流技術,2020,39(3):48-54.
BAI Yangmin, LI Yan. Research on innovation system of? logistics? industrial cluster from ecosystem perspective: Taking Tianjin as example [J]. Logistics Technology, 2020,39 (3): 48-54.
[10]? 李雷,楊懷珍,馮中偉. 供應鏈上游段VMI&TPL模式的利益分配機制——基于最大熵值法與正交投影法的整合視角[J].系統(tǒng)管理學報,2020,29(2):400-408.
LI Lei, YANG Huaizhen, FENG Zhongwei. Profit distribution mechanism of VMI & TPL model at upstream section of supply chain based on the perspective of integration of the maximum entropy method and vertical projection method[J]. Journal of Systems and Management, 2020,29(2):400-408.
[11]? 吳倩,曹光四.基于層次分析法的供應環(huán)節(jié)選擇研究策略[J].廣西質(zhì)量監(jiān)督導報,2020(1):160-161.
[12]? 王凱成,廖吉林.基于AHP和TOPSIS的Y藥品集團物流配送中心選址研究[J].物流工程與管理,2020,42(1):67-69.
WANG Kaicheng, LIAO Jilin. Research on location of logistics distribution center of Y pharmaceutical group based on AHP and TOPSIS[J]. Logistics Engineering and Management, 2020,42 (1): 67-69.
[13]? 王佳蓉. 基于跨階段級聯(lián)失效的集團型企業(yè)供應鏈網(wǎng)絡穩(wěn)定性研究[D].杭州:浙江工商大學,2020.
WANG Jiarong. Research on Supply Chain Network the? Stability? of Group-type Enterprises Based on Cross -stage Cascading? Failure[D].Hangzhou: Zhejiang Gongshang University, 2020.
[14]? 蘇子豪. 供應鏈網(wǎng)絡級聯(lián)故障與脆弱性研究[D].南京:南京郵電大學,2019.
SU Zihao. Research on Cascading Failures and Vulnerabilities of Supply Chain Networks[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2019.
[15]? 張亮星,王少華,張明堯.串聯(lián)可修復供應鏈運行可靠性研究[J].機械設計與制造,2019(11):25-28.
ZHANG Liangxing, WANG Shaohua, ZHANG Mingyao.? Research? on operation reliability of repairable series supply chain[J]. Machinery Design and Manufacture, 2019 (11):? 25-28.
[16]? 范露華. 基于熵權TOPSIS模型的建筑物料供應商評價與管理研究[J].重慶理工大學學報(自然科學),2019,33(12): 240-248.
FAN Luhua. Research on the construction material supplier? evaluation? and management based on entropy weight TOPSIS model[J]. Journal of Chongqing University of Technology (Natural Science), 2019,33 (12): 240-248.
[17]? 趙軍陽,張志利.基于模糊粗糙集信息熵的蟻群特征選擇方法[J].計算機應用, 2009,29(1):109-111.
ZHAO Junyang, ZHANG Zhili. Ant colony feature selection based on fuzzy rough set information theory[J]. Journal of Computer Applications, 2009,29(1):109-111.
[18]? 胡勁松,陳怡寧.多目標問題的逼近于理想解的排序方法研究[J]. 青島大學學報(自然科學版), 2013(1):72-76.
HU Jinsong, CHEN Yining. Techique for multiple objective system order preference by similarity to ideal solution[J]. Journal of Qingdao University(Natural Science), 2013(1): 72-76.
[19]? YILDIZ A, YAYLA Y A. Application of fuzzy TOPSIS and generalized Choquet integral methods to select the best supplier[J]. Decision Science Letters, 2017, 6(2):137-150.
[20]? 孫希彤,劉秋生,王樂軍.基于改進權值和TOPSIS質(zhì)量評估方法[J].計算機測量與控制,2017,25(1):228-231.
SUN Xitong, LIU Qiusheng, WANG Lejun. Method of? quality? assessment based on improved weight and TOPSIS [J]. Computer Measurement and Control, 2017,25 (1): 228-231.
[21]? 韓二東,徐國東.基于直覺模糊交叉熵及灰色關聯(lián)的混合評價信息供應商選擇決策[J].科學技術與工程,2017,17(7):1-9.
HAN Erdong, XU Guodong. Supplier selection decision making method based on intuitionistic fuzzy cross entropy and grey relational[J]. Science Technology and Engineering, 2017,17(7):1-9.
[22]? 趙萌, 邱菀華. 基于混合信息的供應商選擇熵決策模型[C]//統(tǒng)籌優(yōu)選與經(jīng)濟轉(zhuǎn)型——中國管理科學學術年會. 杭州: [s.n.] , 2011:511-517.
[23]? 李曉英. 大型餐飲企業(yè)綠色供應鏈管理的供應商選擇與契約協(xié)調(diào)模型研究[D]. 大連:大連理工大學,2018.
LI Xiaoying. Research on Models of Supplier Selection and Contract Coordination for Green Supply Chain Management of Large-scale Restaurants[D]. Dalian: Dalian University of technology, 2018.