استفاده از روش تصمیم گیری چند هدفه فازی برای ارائه مدل ارزیابی ریسک پروژه (حفاری چاه نفت آذر)
محورهای موضوعی :
مدیریت صنعتی
Mohammad Reza Imani Moghadam
1
(Department of industrial engineering, faculty of engineering, science and research branch of Tehran, Islamic Azad University, Tehran, Iran
Email: Rezaimani2010@gmail.com)
Mohammad Khalil Zadeh
2
(Department of industrial engineering, faculty of engineering, science and research branch of Tehran, Islamic Azad university, Tehran, Iran)
تاریخ دریافت : 1394/10/16
تاریخ پذیرش : 1395/04/28
تاریخ انتشار : 1395/06/04
کلید واژه:
تئوری فازی,
Multi-Objective Decision Making,
fuzzy theory,
ارزیابی ریسک,
Risk Assessment,
تصمیم گیری چند هدفه,
جواب های مؤثر,
Effective Responses,
چکیده مقاله :
مدیریت ریسک پروژه در پروژه ها، نشان دهنده اهمیت رتبه بندی و اولویت بندی ریسک برای تمرکز بیشتر بر مدیریت فعالیت هایی که ریسک بالاتری دارند، است؛ به عبارت دیگر، فعالیت ها براساس ریسک انجام آن ها اولویت بندی و ارزیابی می گردند. در این پژوهش، سعی برآن شده است که برای ارزیابی ریسک احتمالی پروژه، از یک مدل برنامه ریزی فازی با اهداف چندگانه استفاده شود. در این گونه مدل ها جهت بهینه شدن، چند هدف به طور همزمان مورد توجه قرار می گیرند. امکان دارد مقیاس سنجش برای هر هدف با مقیاس سنجش برای اهداف دیگر تفاوت داشته باشد. در مدل مورد مطالعه دو هدف دنبال می شود اولی مینمم کردن هزینه مورد انتظار حاصل از ریسک های مختلف و دومی مینمم کردن زمان مورد انتظار از ریسک های احتمالی است. روش پیشنهادی برای یک مطالعه موردی در پروژه حفاری چاه نفت آذر در منطقه ایلام به کارگرفته شده است که در آن با استفاده از تصمیم گیری چندهدفه و روشL-P متریک به حل مدل مربوطه پرداختیم. در روش L-P متریک با استفاده از توابع سازگار انحرافات موجود در جواب ها را نسبت به جواب ایده آل به حداقل رسانده و مدل دوهدفه موجود به یک مدل تک هدفه تبدیل کرده و حل نمودیم.
چکیده انگلیسی:
Project risk management in projects, illustrate the importance of risk ranking and prioritizing to focus more on the management of higher risk activities; in other words, activities are prioritized and ranked based on the risk of their performance.In this study, it has been tried to use a multi-objective fuzzy planning in order to assess the potential risks of the project. To optimize these models, several objectives simultaneously are considered. The scale for each purpose may be different from the scale for the other purposes. In this model we have two aims: The first one is to minimize the expected cost of various risks and the second one is to minimize the expected time of the possible risks.A proposed method for a case study in Azar oil well drilling project in the region of Ilam is used. We have solved the model by the means of multi-objective decisions and LP metric. In LP metric method, we minimized the deviation in answers compared to ideal answer using the compatible functions and we changed the bi-objective model into single-objective one.
منابع و مأخذ:
Amiri, M. (2010). Provide a way to rank risk project activities using CPM network and fuzzy TOPSIS. Journal of Industrial Management Perspective, 169-183.
Ansarinejad, A., Amalnick, M. S., Ghadamyari, M., Ansarinejad, S., & & Hatami-Shirkouhi, L. (2011). Evaluating the critical success factors in ERP implementing using fuzzy AHP approach. International Journal of Academic Research, 65-80.
Asgharpoor, M. (1997). Multi Criteria Decision Making. Tehran: Tehran University.
Baccarini, D., & Archer, R. (2001). The risk ranking of projects: a methodology. International Journal of Project Management, 139-145.
Boehm, B. W. (1991). Software risk management: principles and practices. Software, IEEE, 32-41.
Ebrahimnezhad, S., Mousavi , S., & Seyrafianpuor, H. (2010). Risk identification and assessment for build–operate–transfer projects: A fuzzy multi attribute decision making model. Expert systems with applications, 575-586.
EmamJome, S., & Ghasemkhani, V. (2010). Fuzzy Logic and it’s important applications in everyday life. Web Magazin, 83-88.
Ghosh, S., & Jintanapakanont, J. (2004). Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach. International Journal of Project Management, 633-648.
JabalAmeli, M., Rezai, S., & Chanibakhsh, A. (200). Project Risk Ranking using multi-criteria decision models. Journal of Industrial management, 125-135.
JafarNezhad, A., & YousefiZenouz, R. (2009). A fuzzy model of ranking risks at petropars company's excavation of oil well projects. Journal of industrial management, 21-38.
KarimiAzari, A., Mousavi, N., Mousavi, S. F., & Hosseini, S. (2011). Risk assessment model selection in construction industry. Expert Systems with Applications, 9105-9111.
Kazemzadeh, A., & Sharifi Mousavi, S. (2011). Developing a fuzzy risk assessment model to assess the schedule risks in construction projects (Case: Track renewal project in Iran railway administration). Expert Systems with Applications, 109-133.
Khatami Firoozabadi, S., & Vafadar Nikjoo, A. (2013). Determining risk category with respect casual relationships between them in fuzzy. Institute for Humanities and Cultural Studies Portable Comprehensive Human Sciences, Management research in Iran, 49-65.
Krane, H. P., Rolstadås, A., & Olsson, N. O. (2010). Categorizing risks in seven large projects—Which risks do the projects focus on? Project Management Journal, 81-86.
Morris, P., & Hough, G. (1987). The Anatomy of Major Projects: A Study of the Reality of Project Management. New York: Wiley.
Nito-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assessment. International Journal of Project Management, 220-231.
Olfat, L., Khosravan, F., & Jalali, R. (2010). Identification and ranking of project risk based on the PMBOK standard by fuzzy approach. Jounal of Industrial MAnagement Studies, 147-163.
SabzehParvar, M. (2007). Project Management. Tehran: Terme .
Salehi Sadaghiani, J. (2010). Provide a method for ranking risks of project activities based on CPM networks using fuzzy and fuzzy TOPSIS methods. Journal of Industrial Management, 69-82.
Sayyadi, A. R., & Azar, A. (2011). Assessing and Ranking Risk in Tunneling Project using Linear Allocation. Journal Industrial Management, 28-38.
Tuncel, G., & Alpan, G. (2010). Risk assessment and management for supply chain networks: A case study. Computer in Industry, 250-259.
Williams, T. (1995). A classified bibliography of recent research relating to project risk management. Europian Journal of Operation Research, 18-38.
Yijian, S., Rufu, H., Dalilin, C., & Hongan, L. (2008). Fuzzy Set - Based Risk Evaluation Model for Real Estate Projects. Tsinghua Science and Technology, 158-164.
Yusefi, O., Naseri, P., & Nill Tabatabi, S. (2014). Project risk assessment models using multi-objective approach to decision making(dam Assaluyeh). Journal of Industrial Engineering, 128-135.
Zayed, T., Amer, M., & Jiayin, P. (2008). Assessing risk and uncertainty inherent in chines highway projects using AHP. International Journal of Project Management, 408-419.
Zeng, J., & Smith, N. (2007). Application of Fuzzy Based Decision Making Methodology to Construction Project Risk Assessment. International Journal of Project Risk Assessment , 589-600.
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Amiri, M. (2010). Provide a way to rank risk project activities using CPM network and fuzzy TOPSIS. Journal of Industrial Management Perspective, 169-183.
Ansarinejad, A., Amalnick, M. S., Ghadamyari, M., Ansarinejad, S., & & Hatami-Shirkouhi, L. (2011). Evaluating the critical success factors in ERP implementing using fuzzy AHP approach. International Journal of Academic Research, 65-80.
Asgharpoor, M. (1997). Multi Criteria Decision Making. Tehran: Tehran University.
Baccarini, D., & Archer, R. (2001). The risk ranking of projects: a methodology. International Journal of Project Management, 139-145.
Boehm, B. W. (1991). Software risk management: principles and practices. Software, IEEE, 32-41.
Ebrahimnezhad, S., Mousavi , S., & Seyrafianpuor, H. (2010). Risk identification and assessment for build–operate–transfer projects: A fuzzy multi attribute decision making model. Expert systems with applications, 575-586.
EmamJome, S., & Ghasemkhani, V. (2010). Fuzzy Logic and it’s important applications in everyday life. Web Magazin, 83-88.
Ghosh, S., & Jintanapakanont, J. (2004). Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach. International Journal of Project Management, 633-648.
JabalAmeli, M., Rezai, S., & Chanibakhsh, A. (200). Project Risk Ranking using multi-criteria decision models. Journal of Industrial management, 125-135.
JafarNezhad, A., & YousefiZenouz, R. (2009). A fuzzy model of ranking risks at petropars company's excavation of oil well projects. Journal of industrial management, 21-38.
KarimiAzari, A., Mousavi, N., Mousavi, S. F., & Hosseini, S. (2011). Risk assessment model selection in construction industry. Expert Systems with Applications, 9105-9111.
Kazemzadeh, A., & Sharifi Mousavi, S. (2011). Developing a fuzzy risk assessment model to assess the schedule risks in construction projects (Case: Track renewal project in Iran railway administration). Expert Systems with Applications, 109-133.
Khatami Firoozabadi, S., & Vafadar Nikjoo, A. (2013). Determining risk category with respect casual relationships between them in fuzzy. Institute for Humanities and Cultural Studies Portable Comprehensive Human Sciences, Management research in Iran, 49-65.
Krane, H. P., Rolstadås, A., & Olsson, N. O. (2010). Categorizing risks in seven large projects—Which risks do the projects focus on? Project Management Journal, 81-86.
Morris, P., & Hough, G. (1987). The Anatomy of Major Projects: A Study of the Reality of Project Management. New York: Wiley.
Nito-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assessment. International Journal of Project Management, 220-231.
Olfat, L., Khosravan, F., & Jalali, R. (2010). Identification and ranking of project risk based on the PMBOK standard by fuzzy approach. Jounal of Industrial MAnagement Studies, 147-163.
SabzehParvar, M. (2007). Project Management. Tehran: Terme .
Salehi Sadaghiani, J. (2010). Provide a method for ranking risks of project activities based on CPM networks using fuzzy and fuzzy TOPSIS methods. Journal of Industrial Management, 69-82.
Sayyadi, A. R., & Azar, A. (2011). Assessing and Ranking Risk in Tunneling Project using Linear Allocation. Journal Industrial Management, 28-38.
Tuncel, G., & Alpan, G. (2010). Risk assessment and management for supply chain networks: A case study. Computer in Industry, 250-259.
Williams, T. (1995). A classified bibliography of recent research relating to project risk management. Europian Journal of Operation Research, 18-38.
Yijian, S., Rufu, H., Dalilin, C., & Hongan, L. (2008). Fuzzy Set - Based Risk Evaluation Model for Real Estate Projects. Tsinghua Science and Technology, 158-164.
Yusefi, O., Naseri, P., & Nill Tabatabi, S. (2014). Project risk assessment models using multi-objective approach to decision making(dam Assaluyeh). Journal of Industrial Engineering, 128-135.
Zayed, T., Amer, M., & Jiayin, P. (2008). Assessing risk and uncertainty inherent in chines highway projects using AHP. International Journal of Project Management, 408-419.
Zeng, J., & Smith, N. (2007). Application of Fuzzy Based Decision Making Methodology to Construction Project Risk Assessment. International Journal of Project Risk Assessment , 589-600.
