انتخاب مکان احداث شعب بانک با رویکرد تئوری مجموعه‌های راف- برنامه‌ریزی آرمانی چند انتخابه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد مدیریت صنعتی ، موسسه آموزش عالی کار، قزوین، ایران.

2 استاد، گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

چکیده

مکانیابی، یک اقدام اساسی در فرایند احداث شعب بانک‌هاست. انتخاب درست مکان تأثیر مستقیمی بر کارایی بانک‌ها داشته است و دستیابی به سایر اهداف را تسهیل می‌کند. عوامل مؤثر درتصمیم‌های مکانیابی زیاد و پیچیده بوده و استفاده از روش‌های سنتی نمی‌تواند پاسخگو باشد، بنابراین نیاز به استفاده ازالگویی مناسب برای مکانیابی شعب بانک‌ها می‌باشد. هدف این تحقیق شناسایی معیارهای مهم مکانیابی شعب بانک‌ها و انتخاب مکان مناسب تأسیس شعب جدید بانک سپه می‌باشد. پژوهش حاضر به لحاظ هدف از نوع کاربردی و از نظر اجرا توصیفی - پیمایشی است. روش تحلیل مورد استفاده، تئوری مجموعه‌های راف و برنامه‌ریزی آرمانی چند انتخابه است، به این صورت که نخست معیارهای مهم مکانیابی با استفاده از پیشینه پژوهش و نظر خبرگان تعیین شد و وزن و اولویت معیارها با استفاده از رویکرد تئوری مجموعه‌های راف به دست آمد، سپس اطلاعات مکان‌های کاندید جمع‌آوری و یک تابع عضویت فازی ایجاد شد که با استفاده از خروجی این تابع، حدود آرمانی و همچنین اولویت‌های به دست آمده، یک مدل برنامه‌ریزی آرمانی فرموله و سپس به کمک نرم‌افزار لینگو حل و بهترین مکان برای تأسیس شعبه جدید بانک سپه مشخص شد. ترکیب تئوری راف و برنامه‌ریزی آرمانی چند انتخابه برای اولین بار در این پژوهش انجام می‌گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

Selection of Bank Branches Location Based on Rough Set Theory – Multi Choice Goal Programming

نویسندگان [English]

  • fatemeh abbasi 1
  • Akbar Alam Tabriz 2
1 Master of Industrial Management, kar Higher Education institute, Qazvin, Iran.
2 Professor, Faculty of Management and Accounting, Shahid beheshti University, Tehran, Iran.
چکیده [English]

Location selection is one of the most important activities in establishment of bank branches. Choosing a suitable location have a direct impact on the performance of banks and also facilitating the achievement of other objectives. There are a lot of influential factors on the location selection which are complicated and therefore the traditional methods cannot be used. So we need to have a suitable model that whereby we can find the proper location for bank branches. The purpose of this research is identifying the important criteria in locating bank branches and selection of appropriate location for established new branches of Sepah bank. This Study is an applied research. The method used to analyze is Rough Set Theory and Multi Choice Goal programming. Initially, important criteria was determined using literature and experts opinion , Then Criteria priority were achieved using RST , Then, the candidate locations information were collected and A fuzzy membership function was created and A Multi choice goal programming model was developed using the membership functions output and criteria priority. The goal programming model was solved by lingo software and determined the best place to establish new branches. The combination of rough set theory and Multi Choice goal programming for the first time has been used in this research.
 

کلیدواژه‌ها [English]

  • Location
  • Rough Set Theory
  • Multi choice Goal Programming
[1]      Rasouli R., Mesgari M., Moradweisi H. (2015) "Bank branches site selection in competitive condition using genetic algorithm"; Survey in Engineering and Geographic Information Journal, 6(21): 4-9.
[2]      Ashournejad G., Faraji Sabokbar H., Alavi Panah S., Nami MH (2011) "Locating new bank branchs and financial and credit institutions using the fuzzy Network Analysis process", Research and Urban Planning Journal, 2(7): 1-20.
[3]      Farzad F., Maddah M., Zarkar A. (2013) "A model for identification and avaluation of agencies and branches location of industrial- services institutes", Journal of Industrial Management Perspective, Tehran, Number 9: 114-134.
[4]      Weon H. E., Eui, H. W., Sik K. Y. (2010) "The study of location strategy for bankthrough the analysis of inter-regional financial transaction network; "International Journal of u- and e- Service, Science and Technology, Vol. 3, No. 1, 21-30.

[5]      Berjisian A., Abedin Darkoosh S. (2012) "Site selection of private banks branches in Tehran's twenty two areas (A case study of Parsian Bank)"; Economic Research, 12(45):55-74.

[6]      Cinar N. (2009) "A decision support model for bank branch location selection"; International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, Vol. 3, No.12:1092-1097.
[7]      Maccarthy B. L. (2003) "Factors affecting location decisions in international operations-a delphi study"; International Journal of Operations and Production Management, Vol. 23, pp.794-818.
[8]      Poladdezh M. (1997) Allocation and efficiency of industrial projects; Pardis Publication, Tehran, Iran
[9]      Litkouhi S., Jahanbakhsh H. Charkhchian M. (2014) Positioning theory; Payam Noor University.
[10]   Rezaei Sangsaraki F. (2013) The choice of location of bank branches through a combination of hierarchical analysis and artificial neural network (case study of Eghtesad Novin bank branches in Tehran); Master's Thesis, Shahid Beheshti University.
[11]   Mehrabi Kooshki A. (2001) Location of industries using MADM decision methods in power plant; (Master's thesis), Tehran University.
[12]   Miliotis P., Dimopoulou M., Giannikos I. (2002) "A hierarchical location model for locating bank branches in a competitive environment"; International Transactions in Operational Research, Vol. 9, No. 5: 549-565
[13]   Jafarnejad A., Esmaelian M., Rezvani M. (2007) "Locating distribution chain using the Nonlinear Integer programming model"; Management Researches in Iran, Tehran, 12(1):105-125.
[14]   Berjisian A., (2006) Site selection of private banks branches in Tehran's twenty two areas (A case study of Parsian Bank); Master's Thesis, Shahid Beheshti University.
[15]   Amiri M., Taghavi Fard, MT, Aghaei M (2016) "Development of Three-Objective Model for the Location – Allocation of Assistance Centers in a probabilistic Condition of availability to emergency Vehicles"; Modern Researches in Decision Making ,Iran,Tehran, 1(2):1-27.
[16]   Jafarnejad A., Asgharizadeh E., Mousavi N. (2002) Prioritize and select appropriate location for branches of the keshavarzi Bank, using hierarchical analysis (AHP), (Master's Thesis),Tehran University.
[17]   Goli A., Olfat L., Fookordi R. (2010) "Location of banking automatic teller machines (ATMs) based on analytic hierarchy process method (AHP) Case study: Keshavarzi Bank ATMs in Tehran Municipality,  District"; Geography and Development Iranian Journal, No., 10, 8(18).

[18]   Khatami firouzabadi MA, Taghavi fard, MT, Allahi Roodposhti S. (2012) "A m for locating branches of, ghavamin bank"; Journal of New Marketing Research, 2(1):129-148.

[19]   Rahgan Sh, Mirzazadeh A. (2012) "A new method in the location problem using fuzzy evidential reasoning"; Research Journal of Applied Sciences, Engineering and Technolog, 4(22): 4636-4645.

[20]   Lotfalipour Z., Naji- Azimi Z., Kazemi M. (2014) "Locating the bank branches using a hybrid method"; Technical Journal of Engineering and Applied Sciences, 4(3):124-134.

[21]   Allahi S., Mobin MS, Vafadarnikjoo A., Salmon C.(2015) "An integrated AHP-GIS-MCLP method to locate bank branches"; Industrial and Systems Engineering Research Conference.
[22]   Fei chen-l, Tsung Tsai-C. (2016) "Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain"; Tourism Management, Vol. 53: 197–20
[23]   Ping Ho-H. ,Ter chang-C and yuan co-C (2013) "On the location selection problem using analytic hierarchy process and multi-choice goal programming"; International Journal of SystemsScience, Vol. 44, No. 1: 94-108.
[24]   Karimi T., Sadeghi Moghadam MR (2014) Rough sets and gray Sets; Second Edition, Mehraban Nashr Book Institute, Tehran, Iran
[25]   Yin Zhai L., Pheng Khoo L., Wei Zhong Z. (2008) "A rough set based QFD approach to the management of imprecise design information in product development"; The Journal of Advanced Engineering Informatics, 23: 222-228.

[26]   Bafandeh A., Rahimi R. (2015) "A fuzzy expert systems for bank real customers' credit rating", Iranian Journal of Trade Studies, Iran, Tehran, 19 (73):1-28.

[27]   Salami Z. (2012) A multi choice goal programming model for R & D project portfolio selection problem Solving; (Master's Thesis), Islamic Azad University, South Tehran.
[28]   Neelavathi N.R (2015) "Research on lexicographic linear goal programming problem based on LINGO and column-dropping rule"; International Journal of Recent Research in Mathematics Computer Science and Information Technology, Vol. 2:314-327