ارائه الگویی هوشمند برای مدیریت پسماند شهری

نوع مقاله : مقاله های برگرفته از رساله و پایان نامه

نویسندگان

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

2 گروه مدیریت صنعتی، واحدفیروزکوه، دانشگاه آزاد اسلامی، فیروزکوه، ایران

3 گروه مدیریت صنعتی، واحد فیروزکوه، دانشگاه آزاد اسلامی، فیروزکوه، ایران

4 گروه اقتصاد، واحد فیروزکوه، دانشگاه آزاد اسلامی، فیروزکوه، ایران

چکیده

یکی از مهم‌ترین راهکارهای مدیریت مناسب پسماند که در حال حاضر به عنوان اولویت اول در مدیریت پسماند شهری در بسیاری از کشورها در کانون توجه قرار گرفته است، مدیریت هزینه‌ها و تفکیک و جدا سازی پسماند در جهت ایجاد درآمد است. تحقیق پیش رو با استفاده از آمار مربوط به جمعیت ساکن، تولید و تفکیک پسماند و به کمک الگوریتم کوانتومی، به ارائه الگویی برای مدیریت پسماند نواحی مختلف منطقه 4 تهران طی ماه‌های مختلف سال‌های 96 پرداخته است. ناحیه 7 با بیش از 182 هزار نفر و ناحیه 8 با بیش از 52 هزار نفر، به ترتیب پر جمعیت و کم جمعیت‌ترین ناحیه منطقه 4 به حساب می‌آیند. ناحیه 7 در سال 96 با تولید پسماند بیش از 4 تن بیشترین میزان تولید پسماند را در بین نواحی نه گانه منطقه 4 داشته است، به گونه‌ای که به تنهایی بیش از 3 برابر ناحیه 9 پسماند تولید کرده است. به طور میانگین می‌توان گفت در سال‌های 96 تقریبا 15/23% از کل پسماند منطقه 4 شهر تهران به صورت تفکیک جمع آوری شده است. در همین سال ناحیه 7 با 73/23% بهترین ناحیه و ناحیه 6 با 34/15 درصد کم کارترین ناحیه در این زمینه بوده است.

کلیدواژه‌ها


عنوان مقاله [English]

Provide an intelligent model for municipal waste management

نویسندگان [English]

  • Ali Khosravi Moghaddam 1
  • Seyed Ahmad Shayannia 2
  • Mohammad Mehdi Movahedi 3
  • Khosrow Azizi 4
1 PhD student in Industrial Management, Islamic Azad University, Firoozkooh Branch, Iran
2 Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
3 Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
4 Department of Economics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
چکیده [English]

One of the most important strategies for proper waste management, which is currently the first priority in urban waste management in many countries, is cost management and waste segregation to generate revenue. The present study, using statistics related to resident population, waste generation and segregation and with the help of quantum algorithm, has provided a model for waste management in different areas of Tehran Region 4 during different months of 1996. District 7 with more than 182,000 people and District 8 with more than 52,000 people are the most populous and least populated areas in Region 4, respectively. District 7 in 1996, with a waste production of more than 4 tons, had the highest amount of waste production among the nine districts of Region 4, so that it alone has produced more than 3 times more waste than District 9. On average, it can be said that in 1996, approximately 23.15% of the total waste in District 4 of Tehran was collected separately. In the same year, District 7 with 23.73% was the best district and District 6 with 15.34% was the least efficient district in this field.

کلیدواژه‌ها [English]

  • Waste Management
  • Waste Generation
  • Quantum Algorithm
  1. Hashemi, Hashem, 1381, Garbage, The Mysterious Reality of Municipalities, Special Note No. 7 on Waste Management.

    Organization for the Recycling and Converting of Municipal Property of Tehran, 2004, Quarterly Report on Solid Waste Management in Tehran, Deputy Head of Education and Research.

    Eskandari Nodeh, Mohammad, 2005, Spatial and spatial analysis of the processes of production, collection and disposal of waste materials in urban society (Case study: Tehran), directed by Dr. Ahmadpour Ahmad, Faculty of Geography, University of Tehran.

    A.Ataullah et al, (2009), “A wave function for stock market returns”, physica A 388, 455-461

    Tania Jafari Nasab, 1393, “Management's assessment of waste source separation in municipal planning approach (Case Study: District 4 of Tehran)”, The Seventh National Conference and Exhibition on Environmental Engineering.

    Solan, W.M. 1993.Site Selection for New Hazardous Waste Mangement Facilites, WHO.

    1. Liu et al, (2012), “An intermediate distribution between Gassian and Cauchy distributions”, physica A, 5411-5421.

    L.A. Cotfas, (2012), “A Quntum Mechanical Model For The Rate of Return, Faculty of Economic Cybernetics, Statistics and Informatics”, ar Xiv: 1211. 1938v1 [q-fin.GN].

    1. Pedram, (2012), “The minimal length uncertainty and the quantum model for the stock market”, ar Xiv: 1111. 6859v2[q-fin. GN].

    Mohammad Sadegh Hassanvand, Ramin Nabizadeh, Mohsen Heidari, 1387, “Analysis of municipal solid waste in Iran”, Journal of Health and Environmental Health Association, Volume I, Issue I, 9-18.

    National Statistical of Iran (http://www.amar.org.ir)

    1. Xu, P.Ch. Ivanov, K. Hu, Z. Chen, A. Carbone, H.E. Stanley, Quantifying signals with power-law correlations: a comparative study of detrending and moving average techniques, Phys. Rev. E 71 (2005) 051101.
    2. Carbone, H.E. Stanley, Directed self-organized critical patterns emerging from coupled fractional brownian paths, Proceedings

    of the Per Bak Memorial Volume, Physica A 340 (2004) 544–551.

    1. Carbone, G. Castelli, H.E. Stanley, Time-dependent hurst exponent in financial time series, Physica A 344 (2004) 267–271.
    2. Carbone, G. Castelli, H.E. Stanley, Analysis of clusters formed by the moving average of a long-range correlated time series, Phys. Rev. E 69 (2004) 026105.
    3. Carbone, H.E. Stanley, Information-theoretical measure for self-organized critical clusters, in: Proceedings of the International Conference on Statistical Machanics, Kolkata; Physica A (2007), accepted for publication.
    4. Chen, P.Ch. Ivanov, K. Hu, H.E. Stanley, Effect of nonstationarities on detrended fluctuation analysis, Phys. Rev. E 65 (2002) 041107-1–041107-15 physics/0111103.
    5. Hu, P.Ch. Ivanov, M.F. Hilton, Z. Chen, R.T. Ayers, H.E. Stanley, S.A. Shea, Proc. Natl. Acad. Sci. USA 101 (2004) 18223.
    6. Chen, K. Hu, P. Carpena, P. Bernaola-Galvan, H.E. Stanley, P.Ch. Ivanov, Effect of nonlinear filters on detrended fluctuation analysis, Phys. Rev. E 71 (2005) 011104.
    7. Chen, K. Hu, H.E. Stanley, V. Novak, P.Ch. Ivanov, Cross-correlation of instantaneous phase increments in pressure-flowfluctuations: applications to cerebral autoregulation, Phys. Rev. E 73 (2006) 031915.