공급업체 선정을 위한 퍼지 TOPSIS 접근방법
Fuzzy TOPSIS Approach for Supplier Selection
0
조회
0
다운로드
14
인용
0
참고문헌
키워드
초록
본 논문의 연구목적은 공급망에서 퍼지 의사결정방법을 적용하여 공급업체 선정문제를 해결하는것이다. 일반적으로 공급업체 선정을 위해서는 품질, 가격, 납기, 공급업체와의 관계 등과 같은 다양한 양적,질적 변수들이 고려되어야한다. 본 논문에서는 위와 같은 변수들을 측정하고 가중치를 부여하기 위해서 언어적 변수를 사용하였으며, 이러한 언어적 측정값은 사다리꼴이나 삼각형 퍼지 수로 나타낼 수 있다. 공급업체 선정문제의 평가기준에 대한 가중치를 도출하고 의사결정자들의 공급업체 평가결과를 통합하기 위해서,퍼지 집합이론과 TOPSIS에 기반을 둔 계층형의 다기준 의사결정모형을 제안하였다. 4가지의 평가기준, 4개 공급업체, 3명의 평가자로 이루어진 사례회사의 공급업체 선정문제에 이 방법을 적용하는 절차를 단계적으로 제시하였다. 결론적으로 본 연구에서 제안한 모형은 공급업체 선정문제에 매우 적합한 것으로 나타났다.
Abstract
Decision-making problem is the process of finding the best option from all of the feasible alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker wants to solve a multiple criteria decision making(MCDM) problem. In general, multi-criteria problems adhere to uncertain and imprecise data, and fuzzy set theory is adequate to deal with it. Since human judgments including preferences are often vague and cannot estimate his preference with an exact numerical value. In decision-making process,very often, the assessment of alternatives with respect to criteria and the importance weight are suitable to use the linguistic variables instead of numerical values. A linguistic decision process is proposed to solve the multiple criteria decision-making problem under fuzzy environment. This paper is aimed to present a fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions usually is complex and unstructured. Many quantitative and qualitative factors such as quality,price, delivery, and relationship with supplier must be considered to determine suitable suppliers. In this paper we have proposed a similarity aggregation method to aggregate fuzzy individual opinions into a fuzzy group consensus opinion, according to their consensus degree coefficient, in MCDM with group decision problems. We consider the difference of importance of each expert as a crisp value in our method. The degree of importance of each expert also can be represented by a linguistic variable; i.e. a fuzzy number. However, if the importance degree of each expert is a fuzzy number,then the aggregation method will not satisfy the consistency requirement. In fact, the fuzzy TOPSIS method is very flexible. According to the closeness coefficient, we can determine not only the ranking order but also the assessment status of all possible suppliers. Significantly, the proposed method provides more objective information for supplier selection and evaluation in supply chain system. The systematic framework for supplier selection in a fuzzy environment presented in this paper can be easily extended to the analysis of other management decision problems. However, improving the approach for solving supplier selection problems more efficiently and developing a group decision support system in a fuzzy environment can be considered as a topic for future research.
참고문헌 (29)
- 김지대, "조합적 생산전략, 학습, 그리고 성과간의 관계에서 가치혁신 전략의 조절 효과", 기업경영연구, 17(2), pp.157~178 (2010), 한국기업경영학회
- 신용백, "한국제조기업 생산관리상의 생산성 저해요인과 그 향상기법 적용현황 및 적용체계 모형 설정연구", 기업경영연구, 12(1), pp.43~59 (2005), 한국기업경영학회
- 장융남, "간판생산 시스템의 최적실행모델링을 위한 간판수 변동요인들에 관한 연구", 기업경영연구, 11(1), pp.151~161 (2004), 한국기업경영학회
- Aissaoui, N., "Supplier Selection and Order Sizing Modeling:A Review", Computer and Operations Research, 34, pp.3516~3540 (2007)
- Belton, V, "Multiple Criteria Decision Analysis: An Integrated Approach" (2002), Kluwer Academic Publications
- Bharadwaj,N, "Investigating the Decision Criteria Used in Electronic Components Procurement", Industrial Marketing Management, 33, pp.317~323 (2004)
- Boer, L. de, "A Review of Method Supplier Selection", European Journal of Purchasing Management, 7, pp.75~89 (2001)
- Chen,C.T, "Extension of the TOPSIS for Group Decision-making Under Fuzzy Environment", Fuzzy Sets and Systems, 114, pp.1~9 (2000)
- Chen, C.-T., "A Fuzzy Approach for Supplier Evaluation and Selection in Supply Chain Management", International Journal of Production Economics, 102, pp.289~301 (2006)
- Chou, S. Y, "Decision Support System for Supplier Based on a Strategy-Aligned Fuzzy SMART Approach", Expert Systems with Applications, 34, pp.2241~2253 (2008)
- Chen, T. Y, "The Interval-Valued Fuzzy TOPSIS Method and Experimental Analysis", Fuzzy Sets and Systems, 159, pp.1410~1428 (2008)
- Dubois, D, "Fuzzy Sets and Systems: Theory and Applications" (1980), Academic Press Inc
- Ha, S. H, "A Hybrid Approach to Supplier Selection for the Maintenance", Expert Systems with Applications, 34, pp.1303~1311 (2008)
- Herrera, F, "Linguistic decision analysis:Steps for solving decision problems under linguistic information", Fuzzy Sets and Systems, 115, pp.67~82 (2000)
- Huang, S. H, "Comprehensive and Configurable Metrics for Supplier Selection", International Journal of Production Economics, 105, pp.510~523 (2007)
- Jahanshahloo, G. R, "Extension of TOPSIS for Decision-making Problems with Interval Data", Mathematical and Computer Modelling, 49, pp.1137~1142 (2009)
- Jahanshahloo, G. R., "An Algorithmic Method to Extend TOPSIS for Decision-making Problems with Interval Data", Applied Mathematics and Computation, 175, pp.1375~1384 (2006)
- Kaufmann, A, "Introduction to Fuzzy Arithmetic: Theory and Applications" (1991), Van Nostrand Reinhold
- Keeney, R. L, "Decision with Multiple Objectives: Preference and Value Trade Offs" (1976), John Wiley and Sons
- Klir G. J, "Fuzzy Sets and Fuzzy Logic: Theory and Applications" (1995), Prentice-Hall Inc
- Meade, L. M, "R&D Project Selection Using the Analytic Network Process", IEEE Transaction on Engineering Management, 49, pp.59~66 (2002)
- Muralidharan, C, "A Multi-Criteria Group Decision Making Model for Supplier Rating", Journal of Supply Chain Management, 38, pp.22~33 (2002)
- Ng,W.L, "An Efficient and Simple Model for Multiple Criteria Supplier Selection Problem", European Journal of Operational Research, 186, pp.1059~1067 (2008)
- Petroni, A, "Vendor Selection using Principle Componebt Analysis", Journal of Supply Chain Management, 36, pp.63~69 (2000)
- Shyur, H.-J, "A Hybrid MCDM Model for Strategic Vendor Selection", Mathematical and Computer Modelling, 44, pp.749~761 (2006)
- Tam, M. C. Y, "An Application of the AHP in Vendor Selection of a Telecommunication System", Omega, 29, pp.171~182 (2001)
- Wang, J.-W, "Fuzzy Hierarchical TOPSIS for Supplier Selection", Applied Soft Computing, 9, pp.377~386 (2009)
- Wang, T.-C, "Application of TOPSIS in Evaluating Training Aircraft Under a Fuzzy Environment", Expert Systems with Application, 33, pp.870~880 (2007)
- Zadeh,L.A, "Fuzzy Sets", Information Control, 8, pp.338~353 (1965)