ABC分析是一種非常普遍以庫存原料依其重要性分類，管理庫存的做法。此分法一般依原料重要性從重要、中等重要、不重要分為A、B、C三類。此分類可針對各類別提供適度的庫存管理。此研究主要透過應用FAHP - TOPSIS模型（“Technique for Order Preferenceby Similarity to Ideal Solution”）論證一套完整的庫存原料分類架構；而所應用之TOPSIS模型主要以相對優劣進行評價，分為肯定的理想目標或稱最優目標及否定的理想目標或稱最劣目標，評價最好的應為與最優目標的距離最近而與最劣目標最遠，透過此方法即可有效達到最終本個案研究庫存原料分類系統的目的。
本研究計畫中之個案公司，為位於台灣苗栗縣之製藥廠。在這項研究中，應用了語意偏好程度的模糊理論評估篩選出重要的準則，透過模糊層次分析法消除層次分析法主觀性的缺憾計算出多準則中個別之權重; 最後，因多標準相矛盾的屬性，所以採用了TOPSI模型做庫存原料的分類。此一系統架構完整地展示了其於庫存原料ABC分類系統的適用性。

ABC analysis, a very common practice used for managing inventory material. The methodology indicated the importance to classify the material by grouping inventory items into Class A, B and C in order to provide appropriate police to inventory management on each assigned class. The study demonstrates a comprehensive framework by applying the model of FAHP-TOPSIS (‘Technique for Order Preference by Similarity to Ideal Solution’), which is a distance-based approach to determine ideal and negative-ideal solution to ultimately achieve the ABC classification for inventory material.
The proposed methodology is applied in a pharmaceutical company situated in Miaoli County, Taiwan. In the study, linguistic fuzzy is applied for determining criteria, Fuzzy AHP method (‘Analytic Hierarchy Process’) is used attempting to eliminate subjectivity during the weighing of multi-criteria; and since multi-criteria with conflicting attribute is taken into account in the case study, using TOPSIS provide the capability for its suitability to rank material into Category A, B, C.

List of Appendices vi
List of Tables vi
List of Figures vii
1 Introduction 1
1.1. Background/ Motivation 1
1.2. Problem Definition 3
1.3. Objectives 5
1.4. Limitation 5
2. Literature Review 8
2.1. ABC classification 8
2.2. Multi-Criteria Decision Making- Inventory Classification 10
2.3. AHP and Fuzzy AHP 16
2.4. TOPSIS Theory 20
3. Research Methods 23
3.1. Study Design 23
3.2. Mathematical Models 26
3.2.1 Fuzzy Theory Application 26
3.2.2 Weighing of Criteria 30
3.2.3 TOPSIS application 33
4 Empirical study 36
4.1. Pharmaceutical Company Case and ABC inventory classification 36
4.2. Determination of criteria 42
4.3. Weighing of criteria 46
4.4. ABC Inventory classification 48
4.4.1 Conventional single criteria and AHP method analysis 49
4.4.2 TOPSIS method analysis 50
4.4.3 Comparison of Conventional, AHP and TOPSIS analysis 52
4.5. Result analysis and findings 56
5 Conclusion 59
5.1. Discussion and conclusion 59
5.2. Recommendations 63
References 65

Balaji K., Senthil Kumar V.S., Multicriteria Inventory ABC Classification in an Automobile Rubber Components Manufacturing Industry, Procedia CIRP 17 ( 2014 ) 463 – 468
Bhattacharya, A., Sarkar, B. and Mukherjee, S.K., ABC analysis in multi-criteria environment—an application of TOPSIS, in 1st International Conference on Logistics & Supply Chain Management, 2001, pp. 489–494.
Bhattacharya Arijit, Sarkar Bijan and Mukherjee Sanat K., Distance-based consensus method for ABC analysis, International Journal of Production Research, Vol. 45, No. 15, 1 August 2007, 3405-3420
Cakir, O. and Canbolat, M.S., A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology, Expert Systems with Applications, 2008, 35 (3), 1367–1378
Celen Aydin, Comparative Analysis of Normalization Procedures in TOPSIS Method: With an Application to Turkish Deposit Banking Market, INFORMATICA, 2014, Vol. 25, No. 2, 185-208, 2014 Vilnius University
Chen, Y., et al., A case-based distance model for multiple criteria ABC analysis. Computers & Operations Research, 2008, 35 (3), 776–796
Chu, Ching-Wu, Liang, Gin-Shuh, Liao, Chien-Tseng, Controlling Inventory by Combining ABC Analysis and Fuzzy Classification, Computers & Industrial Engineering 55 (4), 2008, 841-851
Cohen, M.A. and Ernst, R., Multi-item classification and generic inventory stock control policies. Production and Inventory Management Journal, 1988, 29 (3), 6–8.
Ding, Ji-Feng, An Integrated Fuzzy TOPSIS Method for Ranking Alternatives and Its Application, Journal of Marine Science and Technology, Vol. 19, No. 4, pp 341-352 (2011)
Dyer, J.S., Remarks on the analytic hierarchy process, Management Science, 1990, 36 (3), 249–258.
Easton, A., One-of-a-kind decisions involving weighted multiple objectives and disparate alternatives. In Multiple Criteria Decision Making, edited by J.L. Cochrane and M. Zeleny, pp. 657–667, 1973 (University of South Carolina Press, USA).
Ebrahim Rezaee Nik, Seyed Hessameddin Zehordi, Ahad Nazari, Masatoshi Sakawa, and Fereydoon Honari Choobar, A Combined Fuzzy Analytic Network Process and Fuzzy-TOPSIS Model for Project Risk Assessment, Informatica, 2013, Vol. 24, No 2, 199-217
Ferhan CEBI, A Multiattribute ABC Classification Model Using Fuzzy AHP, Faculty of Management, Istanbul Technical University, Istanbul, Turkey
Flores, B.E. and Whybark, D.C., Multiple criteria ABC analysis, International Journal of Operations and Production Management, 1986, 6(3), 38–46
Flores, B.E. and Whybark, D.C., Implementing multiple criteria ABC analysis. Journal of Operations Management, 1987, 7, 79–84
Flores, B.E., Olson, D.L. and Dorai, V.K., Management of multi-criteria inventory classification. Mathematical and Computer Modeling, 1992, 16, 71–82.
Golam Kabir and Dr. M. Ahsan Akhtar Hasin, Comparative Analysis of AHP and Fuzzy AHP Models for Multicriteria Inventory Classification, International Journal of Fuzzy Logic System (IJFLS) Vol. 1, No.1, October 2011
Golam Kabir and M. Ahsan Akhtar Hasin, Multiple Criteria Inventory Classification Using Fuzzy Analytic Hierarchy Process, International Journal of Industrial Engineering Computations, 3 (2012) 123-132
Golam Kabir and Razia Sultana Sumi, Integrating Fuzzy Delphi with Fuzzy Analytica Hierarchy Process for Multiple Criteria Inventory Classification, Journal of Engineering, Project, and Production Management, 2013, 3(1). 22-34
Guvenir, H.A. and Erel, E., Multi-criteria inventory classification using genetic algorithm, European Journal of Operational Research, 1998, 105 (1), 29–37
Hadi-Vencheh, A., An Improvement to multiple criteria ABC inventory classification, European Journal of Operational Research, 2010, 201(3), 962-965
Hadi-Vencheh A., Mohamadghasemi A., A Fuzzy AHP-DEA Approach for Multiple Criteria ABC Inventory Classification, Expert Systems with Applications 38 (2011) 3346-3352
HOCHSCHULE EMDEN LEER, ABC-Analysis, http://www.hs-emden-leer.de/index.php?id=2745
Jafar Rezaei and Shad Dowlatshahi, A Rule-based Multi-criteria Approach to Inventory Classification, Taylor & Francis Group, International Journal of Production Research, 2010, Vol. 48, No. 23, 7107-7126
Jiang, Ke-Sheng, Multi-Criteria Inventory Classification Using Fuzzy-TOPSIS, National Kaohsiung University of Applied Sciences, 2009
Katica ŠIMUNOVIĆ, Goran ŠIMUNOVIĆ and Tomislav ŠARIĆ, Application of Artificial Neural Networks to Multiple Criteria Inventory Classification, Strojarstvo, 51(4), 313-321
Majid Behzadian, S. Khanmohammadi Otaghsara, Morteza Yazdani, Joshua Ignatius, A state-of the-art survey of TOPSIS applications, Expert Systems with Applications 39 (2012) 13051–13069
Martin W., and Stanford R.E., A methodology for estimating the maximum profitable turns for an ABC inventory classification system, IMA Journal of Management Mathematics, 2007, 18 (3), 223–233
MathWorks, Available from: http://www.mathworks.com/products/fuzzylogic
Mohammad Taghi Taghavifard, and Danial Mirheydari, A New Framework for Evaluation and Prioritization of Suppliers Using A Hierarchical Fuzzy TOPSIS, World Academy of Science, Engineering and Technology, Vol:2 2008-05-23
Morteza Yazdani, Risk Analysis for Critical Infrastructures Using Fuzzy TOPSIS, Journal of Management Research, ISSN 1941-899X, 2012, Vol. 4, No. 1: E6
Partovi, F.Y. and Burton, J., Using the analytic hierarchy process for ABC analysis, International Journal of Production Management, 1993, 13, 29–44.
Partovi, F.Y. and Hopton, W.E., The analytic hierarchy process as applied to two types of inventory problems. Prod. Invent. Mgmt. J., 1994, First Quarter, 13–19
Partovi, F.Y. and Anandarajan, M., Classifying inventory using an artificial neural network approach. Computer and Industrial Engineering, 2002, 41 (4), 389–404
Puente, J., et al., ABC Classification with uncertain data: a fuzzy model vs. a probabilistic model, Applied Artificial Intelligence, 2002, 16 (6), 443–456.
Ramanathan, R., ABC inventory classification with multiple-criteria using weighted linear optimization, Computers & Operations Research, 2006, 33 (3), 695–700
Reynolds, M.P., 1994. Spare parts inventory management. APICS – The Performance Advantage, 4 (4), 42–46.
Rezaei, J., A fuzzy model for multi-criteria inventory classification, In: Proceedings of the 6th international conference on analysis of manufacturing systems (AMS 2007) 11–16 May. May Lunteren: The Netherlands, 2007, 167–172.
Saaty, T.L., How to make a decision: the analytic hierarchy process. Interfaces, 1994, 24, 19–43
Saaty, T.L., Decision-making for leaders; the analytical hierarchy process for decisions in a complex world, Belmont, CA: Wadsworth, 1982.
Shemshadi Ali, Toreihi Mehran, Shirazi Hossein, Tarokh M.J., Supplier Selection based on Supplier Risk: An ANP and Fuzzy TOPSIS Approach, The Journal of Mathematics and Computer Science, Vol. 2 No. 1 (2011) 111-121
Tomislav Volaric, Emil Brajkovic, and Tomo Sjekavica, Integration of FAHP and TOPSIS Methods for the selection of Appropriate Multimedia Application for Learning and Teaching, Internation Journal of Mathematical Models and Methods in Applied Sciences, 2014, Volume 8, 224-232
Velasquez Mark and Hester T. Patrick, An Analysis of Multi-Criteria Decision Making Methods, International Journal of Operations Research Vol. 10, No. 2, 56-66 (2013)
Wong, Wai Peng, Decision Support Model for Inventory Management Using AHP Approach: A Case Study on a Malaysian Semiconductor Firm, California Journal of Operations Management, Volume 8, Number 2, November 2010
Yu, M.C, Multi-criteria ABC analysis using artificial-intelligence-based classification techniques, Expert System with Applications, 2011, 38(4), 3416-3421
Zhou, P. and Fan, L., A note on multi-criteria ABC inventory classification using weighted linear optimization. European Journal of Operational Research, 2007, 182 (3), 1488–1491
張紹勳，多準則決策分析及模糊統計, 五南圖書出版股份有限公司, March, 2012