ارزیابی عملکرد دانشگاه با استفاده از برنامه ریزی آرمانی لکسیکوگراف با رویکرد آموزشی و پژوهشی (مطالعه موردی دانشگاه شاهد)
محورهای موضوعی : مدیریت صنعتی
Saeed Safari
1
(Ph. D in Operation Research, Faculty of Human Sciences, Shahed University)
Hossein Sabzian
2
(M.A Student in management, Faculty of Human sciences, Shahed University)
کلید واژه: Resource allocation, رویکرد کمی, تخصیص منابع, برنامه ریزی آرمانی لکسیکوگرافیک عدد صحیح, Quantitative approach, Integer linear goal programming,
چکیده مقاله :
مؤسسات آموزش عالی اعم از خصوصی و دولتی از مهم‌ترین مؤسسات آموزشی یک کشور محسوب می‌شوند. در این رابطه کیفیت محصولات ( خروجی‌های دانشگاه) بسیار مورد توجه است، توجه دانشگاه‌ها به چنین مقوله‌هایی باعث گردیده است تا عملیات آن‌ها همانند صنایع تولیدی، تجاری محور و سود محور گردد. این رویکرد بر این عقیده استوار است که صنایع تولیدی که تحت نظام‌های کارآیی مدیریت، فعالیت می‌کنند، محصولاتی به مراتب با کیفت تری تولید خواهند کرد. چنین مدلی برای پیاده سازی در محیط دانشگاهی وجود ندارد. بنابراین، مقاله حاضر در صدد ارائه‌ی مدلی برای تحقق این هدف است. ضرایب فنی و مقادیر ثابت مورد استفاده در این مدل همگی بر حسب اطلاعات به دست آمده از تجزیه و تحلیل ریاضی دانشگاه تنظیم شده است. مدل پیشنهادی از نوع برنامه ریزی آرمانی لکسیکوگرافیک عدد صحیح است و شامل36 متغیر تصمیم است که به دو مقوله‌ی متغیرهای منابع دانشگاه ( 15 عدد) و متغیرهای فرآورده‌های دانشگاه (21 عدد) تقسیم شده‌اند. در این مدل تعداد آرمان‌ها 49، محدودیت‌های سخت 7 و متغیرهای عدد صحیح 20 عدد می‌باشد. مقایسه بین جواب‌های مدل و فعالیت‌های فعلی در پایان تحقیق نشان دهنده‌ی آن است که کمیّت بسیاری از منابع و فرآورده‌های موجود در دانشگاه پایین‌تر از حد بهینه بوده به استثناء تعداد کارکنان آموزشی و پژوهشی( s9)، تعداد دانشجویان شبانه کارشناسی(p1 ) و دکترای تخصصی( p9) که در سطح بهینه می‌باشد.
Institutions of higher education (both public and private) are among the most important institutions of a country. Several economic factors have forced them to embark on improving the cost-effectiveness and cost-effectiveness of their activities and the quality of their products (outputs) is strongly expected. Such issues have lead universities to focus on profit-making activities and commercialization like manufacturing industries. This inclination is grounded in the fact that manufacturing industries that work under an efficient management system can produce very high-quality products. In fact, there is no such a model for academic contexts. Therefore, this paper is aimed at offering such a model. The coefficients and constants used in this model have all been extracted based on analyzing research and educational aspects of the University. The proposed model is an integer linear Goal programming model which has 36 decision variables that are broken down into two classes of university sources variables (15) and university products variables. The model also includes 49 Goals, 7 structural constraints, and 20 integer variables. At the end of the paper, the current situation is compared with the recommended one and it shows that many of the variables are suboptimal except variables of research and educational officials ( ), graduate ( ) and Ph.D. ( ) night course students number. The comprehensiveness of this model enables managers to plan the smallest research and educational activities and its solutions can be used by managers as applied guidelines.
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14- MU publications. (2005). Maryland University budgeting Process, 16-40.
15- Nopiah, Z. M. kamaruddin, A. H. Ismail, W. R. Abdullai, S. Ahmad, I. (2007). Modeling University as a Production industry: A Quantitative Approach. Proceedings of the 11th WSEAS International Conference on COMPUTERS, Agios Nikolaos, Crete Island, Greece, 448-455.
16- NU Publications. (1998). State university of New York Report, 42-50.
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18- Publication Office. (2008). China national Report, pp 20-35.
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20- R. G. Schroeder. (1973). A survey of management science in university operations. Management Science, 19 (8), 895-906.
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_||_1- Akin.L. Ogunlade. (2008). Resource Allocation: a multi-model, a multi-goal approach, Economics of Education Review, 27(1).
2- ABS.(2007), Australian Bureau of Statistics, Research and Experimental Higher
3- Caballero R, Francisco Ruiz M, Victoria U, Carlos R. (2006). Interactive Meta Goal Programming, European Journal of Operational Research, 175, 135-154.
4- Caballero, R. Golache T. Gomez T., Molina J and Torrico A. (2001). Efficient Assignment of Financial Resources within a university system: case study of university of Malage”, European Journal of Operation Research,133.
5- CAUC, Association of Universities and colleges of Canada report, (2006).
6- D. Jones, M. Tamiz .(2010). Practical Goal Programming, International Series in Operations Research & Management, Science 141, Springer Science & Business Media, 2-5
7- DME.(2010), Development of Education 2006-2010. Denmark ministry of Education
8- EW Publications. (2003). Eastern Washington university strategic resource allocation model, 38-52
9- G.P. White. (1987). The implementation of management science in higher education administration. Omega 15(4), 283-290.
10- H. Williams. (2005). Planning for Effective Resource Allocations in Universities. American Council on Education, Washington, D.C.
11- HEFCE Publications. (2005). Performance indicators in higher education in The UK
12- Jones. Dylan. (2011). A practical Weight sensitivity algorithm for goal and multiple objective programming, European Journal of operational Research, 213, 238-245.
13- M. Basu, & B. Pal. (2006). A goal programming model for long-range resource planning personnel management in university. Advances in Management Studies 2, (3 & 4), 99-108.
14- MU publications. (2005). Maryland University budgeting Process, 16-40.
15- Nopiah, Z. M. kamaruddin, A. H. Ismail, W. R. Abdullai, S. Ahmad, I. (2007). Modeling University as a Production industry: A Quantitative Approach. Proceedings of the 11th WSEAS International Conference on COMPUTERS, Agios Nikolaos, Crete Island, Greece, 448-455.
16- NU Publications. (1998). State university of New York Report, 42-50.
17- Pal, Bijay Baran, & Sen, Shymal. (2008). A linear goal programming procedure for Academic personnel management problems in university system “IEEE region 10 colloquium and the third international conference on industrial systems. Kharagpur, India, December 8-10, 1-7.
18- Publication Office. (2008). China national Report, pp 20-35.
19- S. M. Lee. (1972). Goal programming for decision analysis. Philadelphia: Auer Bach.
20- R. G. Schroeder. (1973). A survey of management science in university operations. Management Science, 19 (8), 895-906.
21- UNESCO Report. (1999). UNESCO Publication, 10-15.