ارائه یک مدل انتخاب سبد سهام پایدار با تکنیک تحلیل پوششی داده ها، TOPSIS و برنامه ریزی عدد صحیح در بورس اوراق بهادار
محورهای موضوعی : مهندسی مالیصغری رضایی نوکنده 1 , محسن واعظ قاسمی 2
1 - گروه ریاضی، واحد رشت، دانشگاه آزاد اسلامی، گیلان، ایران
2 - گروه ریاضی، واحد رشت، دانشگاه آزاد اسلامی، گیلان، ایران
کلید واژه: تاپسیس, برنامه ریزی خطی, تحلیل پوششی داده ها, انتخاب سبد سهام, نمرات افزایش یافته,
چکیده مقاله :
در دنیای پر رقابت امروزی شرط بقا و حضور در عرصه فعالیت، درست عمل کردن و برخورداری از کارایی و اثربخش بالاست، اینها به دست نمی آید مگر با برنامه ریزی ، نظارت، کنترل و ارزیابی مستمر. در راستای این هدف، سعی شده در این مقاله یک مدل ترکیبی ریاضی برای انتخاب و برنامه ریزی ترکیب بهینه ای از سهم ها با توجه به اهداف و الویت ها ارائه گردد، تا بالاترین سازگاری میان انتخاب نهایی و رتبه بندی اولیه هر سهم بدست آید. مدل ارائه شده شامل سه مرحله و چندین گام است، روش SBM تحلیل پوششی داده ها)DEA( برای بازبینی اولیه سهم ها، تصمیم گیری چند شاخصه ای )TOPSIS) در شرایط عدم قطعیت، برای ارزیابی و رتبه بندی سهم ها در دو مرحله انفرادی و دسته بندی شده و برنامه ریزی خطی عدد صحیح (IP) برای انتخاب بهترین سبد سهام به همراه نمرات افزایش یافته با توجه به اولویت ها و محدودیت های سازمان، بکاررفته است. جمع آوری اطلاعات از سایت های معتبر پنج صنعت فعال خودروسازی، داروسازی، پتروشیمی، سیمان وصنایع غذایی صورت گرفته تا بهترین سبد سهام برای سرمایه گذاری با توجه به اثرگذاری الگوریتم ها و روش ها پیشنهاد شود.
In today's highly competitive world, the condition of survival and participation in the field of activity, functioning and efficient and effective, is not achieved except through continuous planning, monitoring, control and evaluation. In this regard, we tried to present a mathematical hybrid model for selecting and planning an optimal composition of the shares according to the goals and priorities, in order to obtain the highest compatibility between the final selection and the initial ranking of each share. The proposed model consists of three steps and several steps, the SBM method of data envelopment analysis (DEA) (for initial stock revisions, multi-factor decision-making (TOPSIS)) in uncertainty conditions, for the assessment and ranking of shares in two individual steps and categorized and integer linear programming (IP) for choosing the best stock portfolio with increased scores according to the organization's priorities and constraints. Collect information from reputable sites of five industries active automotive, pharmacy, petrochemical, cement and food industries to the best stock portfolio for investment, due to the impact of algorithms and methods.
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[21]Mavrotas,G.,Diakoulaki, D., & Capros, P. (2003). Combined MCDA–IP approach for project selection in the electricity market. Annals of Operations Research, 120,159–170 . [22] Melachrinoudis,E.,&Kozanidis,G.(2002).A mixed integer knapsack model for allocating funds to highway safety improvements. Transportation Research Part A, 36,789–803. [23]Mukherjee,K.,&Bera,A.(1995). Application of goal programming in project selection-A case study from the Indian coal mining industry. European Journal of Operational Research, 82,18–25.
[24] Oral,M.,Kettani,O.,&Cinar,U.(2001).Project evaluation and selection in a network of collaboration: A consensual disaggregation multi-criterion approach. European Journal of Operational Research, 130, 332–346.
[25]Oral, M., Kettani,O.,&Lang,P.(1991). A methodology for collective evaluation and selection of industrial R&D projects. Management Science,37(7),871–885. [26]Pisinger,D.(2001).Budgeting with bounded multiple-choice constraints. European Journal of Operational Research, 129, 471–480.
[27]Salo,A.,Gustafsson,T.,& Ramanathan,R.(2003).Multicriteria methods for technology foresight. Journal of Forecasting,22, 235–255.
[28]Santhanam, R., & Kyparisis,G.J.(1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 89, 380–399. [29] Santhanam, R., Muralidhar, K., & Scniederjans, M. (1989).A zero-one goal programming approach for information system project selection. Omega,17 (6) ,583–593. [30]Tobin, R.L. (1999).A fast interactive solution method for large capital expenditure selection problems. EuropeanJournalofOperationalResearch,116,1–15. [31]Wang, T., & Dyer, J.S. (2012).Acopulas-based approach to modeling dependence in decisiontrees. Operations Research, 60,225–242.
[32]Zanakis, S. H., Mandakovic, T., Gupta, S.K., Sahay, S., & Hong, S. (1995). A review of program evaluation and fund allocation methods within the service and government sectors.Socioeconomic Planning Sciences,29(1),59–79 .
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[1] Moein Eldini, Prasto and Hashemi, Sima (2008) Evaluation of the efficiency of executive units of Iranian customs through data envelopment analysis method, master's thesis. pp. pp. 1-5
[2] Abu-Taleb. M. & Mareschal, B. (1995). Water resources planning in the Middle East: Application of the PROMETHEE V multicriterion method. European Journal of Operational Research, 81,500–511 .
[3] Albright, S. C. (1975). Allocation of research grants to university research proposals. Socio-Economic Planning Sciences, 9(5), 189–195.
[4] Badri, M. A., Davis, D., & Davis, D. (2001). A comprehensive 0–1 goal programming model for project selection.International Journal of Project Management, 19, 243252.
[5] Banker, RD, Charnes, A & Cooper, WW (1984), 'Some models for estimating technical scale inefficiencies in data envelopment analysis', Management Science, vol. 30, no. 9, pp. 1087-92. [6] Banker, R. D.and Thrall, R.M.(1992). Estimation of Returns to Scale Using DataEnvelopment Analysis, European Journal of Operational Research, 62, 74-78.
[7] Belton, V, & Stewart, T. (2002).Multiple criteria decision analysis: An integrated approach.Kluwer Academic Publishers.
[8] Bickel, J. E., & Smith, J. E. (2006). Optimal sequential exploration: A binary learning model. Decision Analysis, 3, 16–32.
[9]Clemen, R.T.,&Reilly,T.(1999).Correlations and copulas for decision and risk analysis. Management Science,45,208–224.
[10] Cook, W. D., & Green, R. H. (2000). Project prioritisation: A resource-constrained data envelopment analysis approach. Socio-Economic Planning Sciences, 34, 85–99.
[11] Fandel, G., &Gal, T.(2001).Redistribution of funds for teaching and research among universities: The case of North Rhine—Westphalia. European Journal of Operational Research, 130,111–120.
[12] Farrell, M. (1957).The measurement of productive efficiency. Journal of the Royal Statistical Society, 120 (3), 253–281.
[13] F. Hosseinzadeh Lotfi, R.Fallahnejad and N.Navidi. Ranking Efficient Units in DEA by Using TOPSIS Method.Applid Mathematical Sciences, Vol.5, (2011) ,no.17,805-815.
[14] Golabi, K., Kirkwood, C. W., & Sicherman, A. (1981). Selecting a portfolio of solar energy projects using multiattribut preference theory. Management Science, 27, 174–189.
[15] Gustafsson,J.,&Salo,A.(2005).Contingent portfolio programming for the management of risky projects. Operations Research,53,946–956.
[16] Kaou, T. (2001). 'Theory and methodology a slacks-based measure of efficiency in data envelopment analysis', European Journal of Operational Research, vol. 130, pp. 498-509.
[17] Kirkwood, C.W. (1997). Strategi cdecision making. Multiobjective decision analysis with spreadsheets. Duxbury Press.
[18] Kwak, N. K., & Lee, C. (1998). A multicriteria decision - making approach to university resource allocation and information infrastructure planning . European Journal of Operational Research, 110, 234–242. [19] Madjid Tavana, Mehdi Keramatpour, Francicco J.Santos-Arteaga, Esmail Ghorbaniane.(2015). A fuzzy hybrid project portfolio selection method using Data Envelopment Analysis, TOPSIS and Integer Programing .Expert Systems With Application 42 ,8432- 8444. [20] Mavrotas,G .,Diakoulaki,D.,&Caloghirou,Y.(2006).Project prioritization under policy restrictions. A combination of MCDA with0–1 programming . Europeanb Journal of Operational Research, 171,296–308 .
[21]Mavrotas,G.,Diakoulaki, D., & Capros, P. (2003). Combined MCDA–IP approach for project selection in the electricity market. Annals of Operations Research, 120,159–170 . [22] Melachrinoudis,E.,&Kozanidis,G.(2002).A mixed integer knapsack model for allocating funds to highway safety improvements. Transportation Research Part A, 36,789–803. [23]Mukherjee,K.,&Bera,A.(1995). Application of goal programming in project selection-A case study from the Indian coal mining industry. European Journal of Operational Research, 82,18–25.
[24] Oral,M.,Kettani,O.,&Cinar,U.(2001).Project evaluation and selection in a network of collaboration: A consensual disaggregation multi-criterion approach. European Journal of Operational Research, 130, 332–346.
[25]Oral, M., Kettani,O.,&Lang,P.(1991). A methodology for collective evaluation and selection of industrial R&D projects. Management Science,37(7),871–885. [26]Pisinger,D.(2001).Budgeting with bounded multiple-choice constraints. European Journal of Operational Research, 129, 471–480.
[27]Salo,A.,Gustafsson,T.,& Ramanathan,R.(2003).Multicriteria methods for technology foresight. Journal of Forecasting,22, 235–255.
[28]Santhanam, R., & Kyparisis,G.J.(1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 89, 380–399. [29] Santhanam, R., Muralidhar, K., & Scniederjans, M. (1989).A zero-one goal programming approach for information system project selection. Omega,17 (6) ,583–593. [30]Tobin, R.L. (1999).A fast interactive solution method for large capital expenditure selection problems. EuropeanJournalofOperationalResearch,116,1–15. [31]Wang, T., & Dyer, J.S. (2012).Acopulas-based approach to modeling dependence in decisiontrees. Operations Research, 60,225–242.
[32]Zanakis, S. H., Mandakovic, T., Gupta, S.K., Sahay, S., & Hong, S. (1995). A review of program evaluation and fund allocation methods within the service and government sectors.Socioeconomic Planning Sciences,29(1),59–79 .
