کاربرد مدل (ISM)جهت رتبه بندی محصولات شوینده صنعتی با استفاده از روش TOPSIS-AHP فازی

برزگر, مجید; نیکنام‌فر, امیرحسین

کاربرد مدل (ISM)جهت رتبه بندی محصولات شوینده صنعتی با استفاده از روش TOPSIS-AHP فازی

نویسندگان

¹ دانشجوی دکتری مدیریت صنعتی، دانشگاه آزاد اسلامی، واحد قزوین، قزوین، ایران

² کارشناس ارشد، دانشگاه آزاد اسلامی،‌واحد قزوین، باشگاه پژوهشگران جوان و نخبگان، قزوین، ایران

چکیده

در دنیای رقابتی عصر حاضر، سازمان‌ها برای رشد و پایداری خود باید به جدیت تلاش نموده و از استراتژی مناسب جهت پیشرفت و حفظ بقای خود بهره‌گیری نمایند. امروزه، محیط پیرامون سازمان‌ها به سرعت در حال تغییر است که می‌توان به تغییرات تنوع تقاضا و نیازهای مشتریان در انتخاب شوینده‌های صنعتی اشاره کرد. در این پژوهش ابتدا به شناسایی معیارهای سنجش شوینده‌های صنعتی پرداخته می‌شود. سپس با استفاده از روش مدل ساختار تفسیری به سطح‌بندی این عوامل و دسته‌بندی آنها پرداخته می‌شود. در پایان، با استفاده از روش تاپسیس فازی برای رتبه‌بندی شش شوینده صنعتی برتر بهره برده می‌شود. نتایج این پژوهش نشان می‌دهد که معیارهایی که از نیروی پیش‌برندگی بیشتر و وابستگی کمتری برخوردارند، در مدل AHP هم از مقدار وزن بیشتری برخوردار شده‌اند. در این پژوهش، برای افزایش کارایی نتایج حاصل از تکنیک تاپسیس فازی وزن داده‌ها با استفاده از روش تحلیل سلسله مراتبی تعیین می‌شود. همچنین، برای تفسیر میزان تاثیر معیار‌ها به‌طور همزمان از مدل ساختار تفسیری بهره برده می‌شود.

کلیدواژه‌ها

20.1001.1.26767562.1398.17.98.5.7

عنوان مقاله [English]

An Application of ISM Model for Ranking the Industrial Cleaning Products Using Fuzzy AHP-TOPSIS

نویسندگان [English]

majid barzegar ¹
amirhossein niknamfar ²

¹ Islamic Republic of Iran Qazvin Province Industry, Mining and Trade Organization

چکیده [English]

In the present competitive world, organizations need to work hard for their growth and sustainability and employ the right strategy to develop and maintain their own survival advantage. Industrial cleaning production companies face with rapidly changing environment including changes in demand and customer needs. In this study, for the first time, the performance measures of industrial cleaning products are first identified. Then, an interpretive structural model (ISM) is used to categorize and classify the measures. Next, an analytical hierarchy process (AHP) is utilized to improve the efficiency of the weighting method used in a fuzzy TOPSIS technique. At the end, the model is employed to rank six detergents. The results show that the measures called “force more winners” and “less dependence” are associated with more weights.

کلیدواژه‌ها [English]

Keywords: TOPSIS
Fuzzy AHP
ISM model
Industrial Cleaning

مراجع

Abo-Sinna, M. A., & Amer, A. H., (2005), "Extensions of TOPSIS for multi-objective large-scale nonlinear programming problems". Applied Mathematics and Computation, 162(1), 243–256.

Alev Taskin Gumus, (2009), "Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology", Expert Systems with Applications, 36, 4067–4074.

Bian W, Yu M., (2006), "Location analysis of reverse logistics operations for an international electrical manufacturer in Asia Pacific region using the analytic hierarchy process". International Journal of Services Operations and Informatics;1(1/2):187–201.

Bright, Daivies, Downes & Sweeting, (1992), “The development of costing techniques and practices:A UK study”, Management Accounting Research, 3.

Chan, F.T.S., Qi, H.J., Chan, H.K., Lau, H.C.W. and Ip, R.W.L., (2002), ‘‘A conceptual model of performance measurements of supply chain’’, Management Decisions, Vol. 41No. 7, pp. 635-42.

Chang, C.-W., Wu, C.-R., & Chen, H.-C., (2008), "Using expert technology to select unstable slicing machine to control wafer slicing quality via fuzzy AHP". Expert Systems with Applications, 34(3), 2210–2220.

Chang, D. Y., (1996), "Applications of the extent analysis method on fuzzy AHP". European Journal of Operational Research, 95(3), 649–655.

Chen C-T, Lin C-T, Huang S-F., (2006), "A fuzzy approach for supplier evaluation and selection in supply chain management". International Journal of Production Economics;102:289–301.

Cheng, C. H., (1997), "Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function". European Journal of Operational Research, 96(2), 343–350.

Chia-Chi Sun, (2010), "A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods", Expert Systems with Applications 37, 7745–7754.

Christopher, M., (1992), Logistics & Supply Chain Management, Pitmans, London.

Christopher, M. and Towill, D., (2001), ‘‘An integrated model for the design of agile supply chains’’, International Journal of Physical Distribution & Logistics Management, Vol. 31 No. 4, pp. 235-46.

Christopher. and Towill, D., (2001), ‘‘An integrated model for the design of agile supply chains’’, International Journal of Physical Distribution & Logistics Management, Vol. 31 No. 4, pp. 235-46.

Dove, R., (1999), ‘‘Knowledge management, response ability and the agile enterprise’’, Journal of Knowledge Management, Vol. 3 No. 1, pp. 1-17.

Fatemeh Torfi a, Reza Zanjirani Farahani, (2010), Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives, Applied Soft Computing 10, 520–528.

Fliedner, G., (2003), ‘‘CPFR: an emerging supply chain tool’’, Industrial Management & Data Systems, Vol. 103 No. 1, pp. 14-21.

Goldman, S.L., Nagel, R.N. and Preiss, K., (1995), Agile Competitors and Virtual Organisations, Van No strand Reinhold, New York, NY.

Govindan Kannana,٭, Shaligram Pokharel b, P. Sasi Kumarc, (2009), A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and Recycling 54, 28–36.

Gunasekaran A, Patel C, Tirtiroglu E. (2001), Performance measures and metrics in a supply chain environment. International Journal of Production and Operations Managemen; 21(1/2): 71–87.

Holweg , M. and Pil, F.K., (2001), ‘‘Successful build-to-order strategies start with the customer’’, Sloan Management Review, Vol. 43 No. 1, pp. 74-83.

Horngren, C.T. S.M. Datar, and G. Foster., (2003), Cost Accounting: A Managerial Emphasis. Prentile-Hall.

Jharkharia, S. and Shankar, R., (2004), ‘‘IT enablement of supply chains: modeling the enablers’’, International Journal of Productivity and Performance Management, Vol. 53 No. 8, pp. 700-12.

Kannan G, Haq AN, Sasikumar P, Arunachalam S., (2008), Analysis and selection of green suppliers using interpretative structural modeling and analytic hierarchy process. International Journal of Management and Decision Making; 9(2): 163–82.

Lee, A. H. I., Chen, W.-C., & Chang, C.-J., (2008), A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 96–107.

Mandal, A. and Deshmukh, S.G., (1994), ‘‘Vendor selection using interpretive structural modeling (ISM)’’, International Journal of Operations&Production Management, Vol. 14 No. 6, pp. 52-9.

Mandal, A., & Deshmukh, S. G., (1994), "Vendor selection using Interpretive Structural Modeling (ISM)". International Journal of Operations and Production Management, 14(6), 52−59.

Mason-Jones, R. and Towill, D.R., (1999), ‘‘Total cycle time compression and the agile supply chain’’, International Journal of Production Economics, pp. 61-73.

Milani AS, Shanian A, Madoliat R., (2005), "The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection". Structural Multidisciplinary Optimization; 29(4):312–8.

Musee, N., Lorenzen, L., & Aldrich, C., (2006), "An aggregate fuzzy hazardous index for composite wastes". Journal of Hazardous Materials, 137(2), 723–733.

Omar, K.; Shohong W., (2002), "Information technology enables meta-management for virtual organizations", International Journal of Production Economics, (75), pp. 127-134.

Sasikumar P, Kannan G., (2008), "Issues in reverse supply chain, part II: reverse distribution issues – an overview". International Journal of Sustainable Engineering b;1(4):234–49.

Shih H-S, Shyur H-J, Lee ES., (2007), An extension of TOPSIS for group decision making. Mathematical and Computer Modelling; 45:801–13.

Shih, H.-S., Shyur, H.-J., & Stanley Lee, E., (2007), An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7–8), 801–813.

Simchi-Levi, D., Kaminski, P., Simchi-Levi, E. and Shankar, R., (2008), Designing and Managing Supply Chain, Tata McGraw-Hill, New Delhi.

Vickery, S. K., Calantone, R., & Droge, C., (1999), "Supply chain flexibility: An empirical study". The Journal of Supply Chain, 35(3), 16−24.

Waddell, D., & Sohal, A. S., (1998), Resistance: A constructive tool for change management. Management Decision, 36(8), 543−548.

Warfield, J. W., (1974), Developing interconnected matrixes in structural modeling. IEEE Transcript on Systems, Men and Cybernetics, 4(1), 51−81.

Yang, T., & Hung, C.-C., (2007), Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23(1), 126–137.

Yu, C. S., (2002), A GP-AHP method for solving group decision-making fuzzy AHP problems. Computers and Operations Research, 29, 1969–2001.

Yusuf, Y. Y., Gunasekaran, A., Adeleye, E. O., & Sivayoganathan, K., (2004), "Agile supply chain capabilities: Determinants of competitive objectives".European Journal of Operational Research, 159, 379−392.

Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A, (1999), "Agile manufacturing: The drivers, concepts and attributes". International Journal of Production Economics, 62, 33−43.