Development of Compound Model for Warehouse Location Using Fuzzy Weighted Average based on the Left and Right Scores and Fuzzy Case Series

Subject Areas : Industrial Management

Jalal  Rezaeenour ¹ (Assistant Professor Department of Industrial Engineering, University of Qom, Iran)
Mona  Torabi ² (Ms.c of Industrial Engineering, Department of Industrial Engineering, University of Qom, Iran)
Nahid  Babaie ³ (Ms.c of Industrial Engineering, Department of Industrial Engineering, University of Qom, Iran)

Received: 2016-02-20 Accepted : 2016-07-18 Published : 2016-08-25

Keywords:

Abstract :

Today reverse logistics has become one of the most challenging issues in the areas of the automotive supply chain. Therefore, understanding the factors that influence the implementation of reverse logistics is important. We can point to the reasons why organizations pay attention to this subject: Competitive incentives, direct economic incentives, and environmental reasons. In many cases, there are certain rules and regulations in the areas returns that have forced the organizations to pay more attention to this sector. In this research, we determined primary criterions with collecting determined criterions of previous studies and also taking experts’ opinions which consists 3 economical, environmental and social criterions and 19 sub criterions. Then these factors were given to experts in the form of a questionnaire. The collected data were analyzed with the confirmatory factor analysis method. Finally, a number of factors have been removed and the final factors remained. In order to rank the factors, these factors were given to experts in the form of ANP (Network Analysis Process) questionnaire again. Then we used fuzzy ANP method for measuring interdependencies and criterions ranking.

References:

1. Ahmadijazi, R. (2006). The reasons for the delay of development projects in Iran and ways out of it (Master’s dissertation). Iran university of science and technology.


2. Ahmed, S., & Azher, S., & Castillo, M., & Kappagantula, P. (2002). Construction delays in Florida; an empirical study. International Journal of Project Management, 46-53.


3. Aliyadollahzadehtabari, N., & Rahmani, M. (2012). The factors affecting the delay in implementing development projects tract in Mazandaran province. The first regional conference on research and innovative solutions in accounting and management. Tonekabon, Shafagh Institute of Higher Education.


4. Ardit, D., & Pattanalitchamroon, T. (2006). Selecting a delay analysis method in resolving construction claims. International Journal of Project Management, 24(2), 145-155.


5. Ataei, N. (2004). Contractors and oil industries. Syndicate of Iran construction companies monthly magazine (Payam-E-Abadgaran), 207, 35.


6. Bezan, A., & Hemmati, S., & Sadatshariatpanahi, Z. (2011). Check the main causes for delays projects and studies in Semnan province. The Sixth National Congress of Civil Engineering. Semnan, Semnan University.


7. Biuseh, R., & Momeni, M., & Hamidizadeh, M. R. (2011). Identify weaknesses and problems of local companies in the Oil & Gas EPC projects using AHP. The third national conference with a view to removing barriers and improving internal power production in terms of sanctions. Tehran, Sharif University of Technology Research Center.


8. Elbeltagi, E., & Hegazy, T., & Grierson, D. (2005), Comparison among five evolutionary-based Optimization algorithms. Advanced Engineering Informatics, 19(1), 43-53.


9. Eshtehardiyan, E. A., & Nasrazadani, S.M., & Safavi, S. A., & Alikhani, A. (2010). Investigate the causes of delay since the implementation of urban development projects according to the project.  International Project Management Conference. Tehran, Ariana Research Group.


10. Fallahtafti, H., & Ebrahimidehaj, M., & Rafiei, A. (2011). Investigate the causes of delay in implementation of projects and development schemes (Case Study: Yazd Regional Electric Company). Twenty-sixth International Conference on Electricity. Tehran, Tavanir Co.


11. Finke, M.R. (1999). Window analyses of compensable delays. Journal of Construction Engineering and Management Asce, 125(2), 96-100.


12. Golenko-Ginzburg, D., & Gonik, A., & Laslo, Z. (2003). Resource constrained scheduling simulation model for alternative stochastic network Projects. Mathematics and Computers in Simulation, 63 (2), 105-117.


13. Huemann, M. (2010). Considering Human Resource Management when developing a Project-oriented company: Case study of a telecommunication company. International Journal of Project Management, 28 (4), 361-369.


14. Jafari, M., & Nouri, S., & Gandomi, N. (2009). Investigate the causes of delay in construction projects (case study sealants industry Kermanshah Province). Fifth International Conference on Project Management. Tehran, Ariana Research Group.


15. Kao, C. K., & Yang, J. B. (2009). Comparison of windows-based delay analysis methods, International Journal of Project Management, 27 (4): 408-418.


16. Karimipour, H., & Zoghi, H. (2015). Effective indices projects delay case study on the master plan of water supply villages in the province of Gilan. National Conference On Architecture Engineering, Civil and Urban Development. Mazandaran, Kome elmavaran danesh R.S. Institute.


17. Mansfield, N., & Ugwu, O., & Doran, T. (1994). Causes of delay and cost overruns in Nigerian construction Projects. International Journal of Project Management, 12(1), 254-260.


18. Marzouk, M., & El-Dokhmasey, A., & El-Said, M. (2008). Assessing construction engineering-related delays: Egyptian perspective. Journal of Professional Issues in Engineering Education and Practice, 134 (2), 315-326.


19. Mehryari, H. A. (2007). Important items of claims contracting contracts. Tadbir Journal, 18(185), 59.


20. Miri, M., & Khaksefidi, M., & MohammadiRamaghani, Z. (2015). Causes of delay in the implementation of construction projects. International Conference on Economics, Management and Social Sciences, Barcelona-Spain.


21. Mizani, GH. (2003). Regulations governing the role and mission of technical-social development in developing countries. Majlis & Rahbord scientific research-quarterly journal, 39(10), 69_80.


22. Niknamsaeidi, KH., & Herischian, M. (2010). Provide an algorithm for analyzing delays in construction projects and determine the contribution of each factor. Sixth International Conference on Project Management. Tehran, Ariana Research Group.


23. Nouri, S., & Faraji, H. R. (2009). Study of factors delayed construction projects and provide a model to reduce latency. Fifth International Conference on Project Management. Tehran, Ariana Research Group.


24. Odeh, A., & Battaineh, H. (2002). Causes of construction delay: traditional Contracts. International Project Management, 20(1), 67-73.


25. Right, R. E. (2010). A Lighthearted, Serious Look at America's Economic Ills, Florida: MC Graw hill.


26. Salehi, M., & Pirabbasi, M. A. (2015). Identify and prioritize the causes of delayed projects similar to the oil and gas industry using fuzzy ideal option. The second International Conference on Management in the 21st Century. Tehran, Institute of Directors thinker Vieira capital.


27. Sambasivan, M., & Soon,Y. W. (2007). Causes and effects of delays in Malaysian construction industry, International Journal of Project Management, 25(5), 517-526.


28. Taghizadeh, H., & Tari, GH. (2012). A ghraphical model for research method in humanities (4rd ed.). Tehran: Hafiz Publishing.


29. The Hindu (2007). Hit by delays and cost escalation. http://www.hindunnet.com /2007/07/06/stories/2007070657310100>.


30. Vatankhah, R. (2003). Study of Delayed projects-research projects of modernization of the country's schools (Master’s dissertation). Tarbiat Modares University.


31. Williams, T. (2003). Assessing Extension of Time delays on major Projects. International Project Management, 21(1), 19-26.


32. Yang, J. B., & Wei, P . R. (2010). Causes of delay in the planning and design phases for construction projects. Journal of Architectural Engineering, 16(3), 80-83.

1. Esmaielpour, R. (2015). risk ranking of customer relation management with combination mOdel of fuzzy multi criteria decision making techniques. Operation research and applications magazine


2. Ahadi, H., Ghazanfarirad, F.(2010). Propose a hybrid model of fuzzy multi-criteria decision-making methods for determining the location of specialized industrial park rail. Operation reserarch and applications magazine


3. Jabal Ameli, M. (2008) propose a locating assigning model for sensitive facilities - industrial engineering and production management magazine.


4. Ziari, K. (2011). Locating buried solid waste by using AHP model. Journal of Geography and Environmental Studies.


5. Sepehri, M. (2012) Model reintegration ambulances location is found. International Journal of Industrial Engineering & Production Management.


6. Mohammadi Soleimani, M. (2013). A model of the managers of industry organizations, industry, mine and trade using the HP fuzzy.
   
   
   
   1. Alavipoor. F.S. (2016). A geographic information system for gas power plant location using analytical hierarchy process and fuzzy logic, Global J. Environ. Sci. Manage 2(2) 197-207.
   
   
   2. Charnetski. J.R, Multiple criteria decision making with partial information: a site selection problem, in: Space Location-Regional Development, Pion, London, 1976, 51–62Article
   
   
   3. Chang. P.T & Hung. K.C. (2004). Applying the Fuzzy-Weighted-Average Approach to Evaluate Network Security Systems, Computers and Mathematics with Applications 49 (2005), 1797-1814.
   
   
   4. Fortenberry. J.C & Mitra. A, A multiple criteria approach to the location–allocation problem, Computer and Industrial Engineering 10 (1986), 77–87.
   
   
   5. Hakimi. S.L, Optimal locations of switching centers and the absolute centers and medians of a graph, Operations Research 12 (1964), 450–459.
   
   
   6. Liu. F. (2008). Aggregation Using the Fuzzy Weighted Average as Computed by the Karnik–Mendel Algorithms, Ieee Transactions On Fuzzy Systems 16.
   
   
   7. Mokhtarian. M.N. (2011). A new fuzzy weighted average (FWA) method based on left and right scores: An application for determining a suitable location for a gas oil.
   
   
   8. Shaverdi. M. (2014). Application of Fuzzy AHP Approach for Financial Performance Evaluation of Iranian Petrochemical Sector, Procardia Computer Science 31(2014),  995 – 1004
   
   
   9. Lee. H & Park. D, An efficient algorithm for fuzzy weighted average, Fuzzy Sets and Systems 87 (1997), 39-45.
   
   
   10. Chang Chu. T & Nguyen. P.A.H, A Centroid Based Fuzzy Weighted Average for Ranking Alternatives (2014).