ارزیابی و اولویت بندی گازهای آلاینده کارخانه سیمان بر اساس مدلهای FDH و CRA
الموضوعات :
فاطمه دادخواه
1
(گروه ریاضی، واحد مرودشت، دانشگاه آزاد اسلامی، مرودشت، ایران)
محمدرضا مظفری
2
(گروه ریاضی، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران)
جواد گرامی
3
(گروه ریاضی، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران)
الکلمات المفتاحية: Central resource allocation, Free disposal hull, Data Envelopment Analysis, TOPSIS,
ملخص المقالة :
در بسیاری از کشورها کنترل و کاهش میزان آلودگی های محیط زیست بسیار حائز اهمیت می باشد. در این مقاله بر اساس نظر کارشناسان، گازهای آلاینده در صنعت سیمان مشخص شده و بر اساس مدلهای تحلیل پوششی داده ها کنترل و فیلتر کردن این گازها اولویت‌بندی شده اند. با دو مدل شعاعی و غیرشعاعی پیشنهادی، کاهش مجموع هزینه ها و تاثیرات گازهای آلاینده و با یک مدل غیر شعاعی پیشنهادی دیگر، کاهش هزینه و تاثیرات گازهای آلاینده اولویت بندی شده است. این گازهای آلاینده، بر اساس مدلهای FDH و تخصیص منابع مرکزی، نیز با در نظر گرفتن نوع بیماری و هزینه، اولویت بندی شده است. در خاتمه نتایج اولویت‌بندی گازهای آلاینده صنعت سیمان فارس با سه مدل پیشنهادی و روش تاپسیس ومدل FDH مقایسه شده است.
[1] Charnes A., Cooper W.W., Rhodes E., 1978, Measuring the efficiency of decision making units, European Jouenal of Operational Research 2, 429-444.
[2] Banker R.D., Charnes A., Cooper W.W., 1984, Some Model for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science 30, 1078-1092.
[3] Deprins, D., Simar, L., Tulkens, H., 1984, Measuring labor efficiency inpost offices. In M. Marchand, P. Pestieau, H. Tulkens (Eds.), The performance of public enterprises: Concepts and measurements. Amsterdam: North Holland.
[4] Podinovski, V.V., 2004, On the linearization of reference technologies for testing returns to scale in FDH models, European Journal of Operational Research, 152, 800–802.
[5] Soleimani-damaneh M., Reshadi M., 2007, A polynomial-time algorithm to estimate returns to scale in FDH models, Computers & Operations Research 34, 2168–2176.
[6] Soleimani-damaneh M., Mostafaee A., 2015, Identification of the anchor points in FDH models, European Journal of Operational Research, 246, 936–943.
[7] García-Romero A., Santín D., Sicilia G., 2016, Another brick in the wall: a new ranking of academic journals in Economics using FDH ,Scientometrics, 107, 91–101.
[8] Golany B., Phillips F.Y., Rousseau J. J., 1993, Models for Improved Effectiveness Based on DEA Efficiency Results, IIE Transactions 25(6) 2–10.
[9] Golany B., Tamir E., 1995, Evaluating Efficiency-Effectiveness-Equality Trade-offs: A Data Envelopment Analysis Approach, Management Science 41(7) 1172–1184.
[10] Lozano, S., Villa G., 2004, Centralized Resource Allocation Using Data Envelopment Analysis, Journal of Productivity Analysis, 22, 143–161.
[11] Hwang C.L., Yoon K., 1981, Multiple attribute decision making: Methods and applications, Spring, NewYork.
[12] Chen S., Hwang C., 1992, Fuzzy Multiple Attribute Decision Making Methods and Applications, Springer-Verlag Berlin Heidelberg
[13] Yue Z., 2011, An extended TOPSIS for determining weights of decision makers with interval numbers, Knowledge-Based Systems 24, 146–153.
[14] Behzadian M., Khanmohammadi Otaghsara S., Yazdani M., Ignatius J., 2012, A state-of the-art survey of TOPSIS applications, Expert Systems with Applications 39, 13051–13069.
[15] Shanon C.E., 1948, A mathematical theory of communication, Bell System Technival Journal, 27, 379-423.
[16] World Health Organization, 2011, Air pollution report, An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city, Energy, 37, 673-688.
[17] Bevilacqua M., Braglia M., 2002, Environmental Efficiency Analysis for ENI Oil refineries, Journal of Cleaner Production, 10(1) 85-92.
[18] Kumar Mandal S., Madheswaran S., 2009, Environmental Efficiency of The Indian Cement Industry: an Interstate Analysis; The Institute for Social and Economic Change, Bangalore, working paper 227.
[19] Benhelal E., Rafiei A., Shamsaei E., 2012, Green Cement Production: Potentials and Achievements, International Journal of Chemical Engineering and Applications, 3(6) 407-409.
[20] Oguntoke O., Awanu A.E., Annegarn H.J., 2012, Impact of cement factory operations on air quality and human health in Ewekoro Local Government Area, South-Western Nigeria, International Journal of Environmental Studies, 69(6), 934–945.
[21] Zand Hessami H., Golsefid-Alavi M., Madan Shekaf S., Kiani Mavi R., 2012, Evaluation of Success Factors of ISO 14001- Based EMS Implementation and Ranking the Cement Industry Using the TOPSIS Method, Journal of Applied Environmental and Biological Sciences, 2(10) 523-530.
[22] Wang K., Yu S., Zhang W., 2013, China’s Regional Energy and Environmental Efficiency: a DEA Window Analysis Based Dynamic Evaluation. Mathematical and Computer Modelling, 58, 1117-1127.
[23] Sana S., Bhat G.A., Mehraj Balkhi H., 2013, Health Risks associated With Workers in Cement Factories, International Journal of Scientific and Research Publications, 3(5) 2250-3153.
[24] Oyinloye M.A., 2015, Environmental Pollution and Health Risks of Residents Living Near Ewekoro Cement Factory, Ewekoro, Nigeria, International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering, 9(2) 108-114.
[25] Lozano S., 2015, A joint-inputs Network DEA approach to production and pollution-generating technologies, Expert Systems with Applications 42, 7960–7968.
[26] Abbasi M., Kaviani M.A., 2016, Operational efficiency-based ranking framework using uncertain DEA methods, Management Decision, 54(4) 902 – 928.
[27] Liu X., Yuan Z., Xu Y., Jiang S., 2017, Greening cement in China: A cost-effective roadmap, Applied Energy 189, 233–244.
