نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناس ارشد،‌دانشگاه آزاد اسلامیِ، واحد علوم تحقیقات، مهندسی صنایع ، تهران، ایران

2 استادیار دانشگاه آزاد اسلامی ، واحد علوم و تحقیقات، گروه مهندسی صنایع،‌تهران، ایارن

چکیده

این مقاله یک راه حل جهت تخصیص نقدینگی محدود به پیمانکاران بر اساس اولویتهای پروژه که یکی از مباحث مطرح در مدیریت نقدینگی پروژه ها می باشد، ارائه می کند. هدف از این تحقیق ارائه یک راهکار جهت حل مشکلات پیمانکاران عمومی در تخصیص منابع به پروژه های نفت و گاز می باشد. در این مقاله ابتدا شاخصهای اثر گذار بر عملکرد پیمانکاران، با استفاده از روش AHP فازی تعیین می شود. سپس، وزن معیارهای مربوطه محاسبه و امتیاز نهایی پیمانکاران با استفاده از روش TOPSIS بر اساس شاخصهای مذکور تعیین می گردد و در ادامه، پیمانکاران رتبه بندی می شوند. در نهایت، با استفاده از یک الگوریتم ابتکاری نحوه تخصیص نقدینگی محدود در دست به پیمانکاران ارائه می گردد. جهت تشریح روش، از اطلاعات واقعی مربوط به یک پیمانکار عمومی فعال در حوزه نفت و گاز استفاده شده است. در پایان، نتایج ارائه شده در خصوص مسئله مورد نظر و همچنین پیشنهادهای توسعه ای ارائه گردیده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Assigning limited resources to contractors with FAHP and TOPSIS methods

نویسندگان [English]

  • mehdi sadati 1
  • mohammad khalilzadeh 2

چکیده [English]

This paper propose a solution method for assigning limited liquidity to contractors based on the project priorities which is one of the current issues in project liquidity management. The aim of this research is to introduce an approach to resolve the problems of public contractors in assigning resources to oil and gas projects. In this paper, first the effecting indices on contractors' performance are determined by Fuzzy AHP method. Then, the importance weights of the related criteria are calculated and the final scores of the contractors are found by TOPSIS technique based on the indices. Afterwards, the contractors are ranked. At the end, the method of assigning limited liquidity to the contractors is introduced using a heuristic algorithm. The actual data of a public contractor in oil and gas industry are used to illustrate the proposed procedure. Finally, the results and suggestions for further improvement are shown.

کلیدواژه‌ها [English]

  • multi-criteria decision making
  • resource assignment
  • TOPSIS
  • FUZZY AHP
  • oil and gas and petrochemical

Ayhan, M.B.; Kilic, H.S. (2015), “A two stage approach for supplier selection problem in Multi-supplier environment with quantity discounts”, Computers & Industrial Engineering, doi: http://dx.doi.org/10.1016/j.cie.2015.02.026

Beikkhakhian, Y.; Javanmardi, M.;  Karbasian, M.; Khayambashi, B. (2015), “The application of ISM model in evaluating agile supplier’s selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods”, Expert Systems with Applications, 42, pp. 6224-6236

Buckley, J. J. (1985), “Fuzzy hierarchical analysis”, Fuzzy Sets and Systems, 17, pp. 233–247.

Cebeci, U. (2009), “Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard”, Expert Systems with Applications, 36, pp. 8900-8909.

Celik, M.; Er, I. D.; Ozok, A. F. (2009), “Application of fuzzy extended AHP methodology on shipping registry selection: The case of Turkish maritime industry”, Expert Systems with Applications, 36, pp. 190-198.

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

Chang, N. B.; Chang, Y. H.; Chen, H. W. (2009), “Fair fund distribution for a municipal incinerator using GIS-based fuzzy analytic hierarchy process”, Journal of Environmental Management, 90, pp. 441-454.

Deng, H.; Yeh, C. H.; Willis, R. J. (2000), “Inter-company comparison using modified TOPSIS with objective weights”, Computers & Operations Research, 27, pp. 963–973.

Ertuğrul, İ.; Karakaşoğlu, N. (2009), “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, 36, pp. 702–715.

Feng, C. M.; Wang, R. T. (2000), “Performance evaluation for airlines including the consideration of financial ratios”, Journal of Air Transport Management, 6, pp. 133-142.

Gumus, A. T. (2009), “Evaluation of hazardous waste transportation firms by using a two-step fuzzy-AHP and TOPSIS methodology”, Expert Systems with Applications, 36, pp. 4067–4074.

Holt G. D.; Olomolaiye, P.O.; Harris, F. C. (1995), “A Review of Contractor Selection Practice in the UK Construction Industry”, Building and Environment, 30(4), 553-561

Holt, G.D. (1998), “Which contractor selection methodology?” International Journal of Project Management. 16(3), 153-164

Holt, G.D.  (2010), “Contractor Selection Innovation: examination of two decades' published research”. Construction Innovation: Information, Process, Management 10(3), 304-328

Hwang, C. L.; Yoon, K. (1981), “Multiple attributes decision making methods and application”, Springer, Berlin Heidelberg,

Ibadov, N. (2015), “Contractor selection for construction project, with the use of fuzzy preference relation”, Procedia Engineering. 111, 317-323

Kahraman, C.; Ruan, D.; Dogan, I. “Fuzzy group decision-making for facility location selection”, Information Sciences, 157, (2003), pp. 135–153.

Kusumawardani, R.P.; Agintiara. M. (2015), “Application of Fuzzy AHP-TOPSIS Method for Decision Making in Human Resource Manager Selection Process”, Procedia Computer Science, 72, pp. 638-646

Kog, F.; Yaman, H. (2014) “A meta classification and analysis of contractor selection and prequalification”. Procedia Engineering. 85, 302-310

Kumaraswamy, M. M. (1996) , “Contractor Evaluation and Selection: a Hong Kong Perspective”,

Building and Environment, 31(3), 273-282.

Lathman, S. M.  (1994) Constructing the team: Joint Review of Procurement and Contractual Arrangement in the United Kingdom Construction Industry, London; HSMO.

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

Lee, S. K.; Mogi, G.; Kim, J. W.; Gim, B. J. (2008b), “A fuzzy analytic hierarchy process approach for assessing national competitiveness in the hydrogen technology sector”, International Journal of Hydrogen Energy, 33, pp. 6840-6848.

Lin, M. C.; Wang, C. C.; Chen, M. S.; Chang, C. A. (2008), “Using AHP and TOPSIS approaches in customer-driven product design process”, Computers in Industry, 59, pp. 17–31.

Naghadehi, M. Z.; Mikaeil, R.; Ataei, M. (2009), “The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm Bauxite Mine, Iran”, Expert Systems with Applications, 36, pp. 8218-8226.

Önüt, S.; Soner, S. (2008), “Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment”, Waste Management, 28, pp. 1552–1559.

Prakash, C.; Barua, M.K. (2015), “Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment”, Journal of Manufacturing Systems, 37, Page pp. 599-615

Russel, J.S. (1992), “Decision models for analysis and evaluation of construction contractors”, Construction Management and Economics, 10(3), 185-202

Sawalhi, N. EL-; Eaton, D.; Rustom, R. (2007), “Contractor Pre-qualification model: state-of-art”, International Journal of Project Management. 25 (5), 465-474

Serami, M.; Mousavi, S. F.; Sanayei, A. (2009), “TQM consultant selection in SMEs with TOPSIS under fuzzy environment”, Expert Systems with Applications, 36, pp. 2742–2749.

Shyur, H. J.; Shih, H. S. (2006), “A hybrid MCDM model for strategic vendor selection”, Mathematical and Computer Modelling, 44, pp. 749-761.

SLUB (2013). http://www.slib-dresden.de/recherche/datenquellenLst. Acc.:29.11.2013

Taylan, O.; Kabli, M.R.; Saeedpoor, M.; Vafadarnikjoo, A. (2015),  “ Commentary on Construction projects selection and risk assessment by Fuzzy AHP and Fuzzy TOPSIS  methodologies”, Applied Soft Computing,  36,  pp. 419-421

Tiryaki, F.; Ahlatcioglu, B. (2009), “Fuzzy portfolio selection using fuzzy analytic hierarchy process”, Information Sciences, 179, pp. 53-69.

Van Laarhoven, P. J. M.; Pedrycz, W. (1983), “A fuzzy extension of Saaty’s priority theory”, Fuzzy Sets and Systems, 11, pp. 199-227.

Wang, T. C.; Chang, T. H. (2007), “Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment”, Expert Systems with Applications, 33, pp. 870–880.

Wang, Y. J. (2008), “Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan”, Expert Systems with Applications, 34, pp. 1837-1845.

Wang, Y. M.; Elhag, T. M. S. (2006), “Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment”, Expert Systems with Applications, 31, pp. 309–319.

Webber, S. A.; Apostolou, B.; Hassell, J. M. (1996), “The sensitivity of the analytic hierarchy process to alternative scale and cue presentations”, European Journal of Operational Research, 96, pp. 351-362.

Wu, F. G.; Lee, Y. J.; Lin, M. C. (2004), “Using the fuzzy analytic hierarchy process on optimum spatial allocation”, International Journal of Industrial Ergonomics, 33, pp. 553–569.

Wu, H. Y.; Tzeng, G. H.; Chen, Y. H. (2009), “A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard”, Expert Systems with Applications, 36(6), pp. 10135-10147.

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

Yoon, K.; Hwang, C. L. (1985), “Manufacturing plant location analysis by multiple attribute decision making: Part II. Multi-plant strategy and plant relocation”. International Journal of Production Research, 23(2), pp. 361–370.

Zahedi, F. (1986), “The analytic hierarchy process: a survey of the method and its applications”, Interface, 16, pp. 96-108.

Zare, k.; Mehri, J.;  Karimi S. (2015), “A SWOT framework for analyzing the electricity supply chain using an integrated AHP methodology combined with fuzzy-TOPSIS”, International Strategic Management Review, 3, pp. 66-80