USING WEIGHTED MAXIMAL COVERING MODEL WITH PARTIAL COVERAGE AND GEOGRAPHICAL INFORMATION SYSTEMS FOR LOCATING BANK BRANCHES

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MOHAGHAR ALI; ARYAEE SARA; HEIDARY JALIL; TOOMANIAN ARA

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Journal: JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES Year:2018 | Volume:15 | Issue:47 Page(s): 1-22

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Title

USING WEIGHTED MAXIMAL COVERING MODEL WITH PARTIAL COVERAGE AND GEOGRAPHICAL INFORMATION SYSTEMS FOR LOCATING BANK BRANCHES

Author(s)

MOHAGHAR ALI | ARYAEE SARA | HEIDARY JALIL | TOOMANIAN ARA | Issue Writer Certificate

Keywords

LOCATINGQ2

BANK BRANCHESQ2

GEOGRAPHICAL INFORMATION SYSTEM (GIS)Q2

WEIGHTED MAXIMAL COVERING PROBLEM WITH PARTIAL COVERAGEQ1

Abstract

Nowadays banks, credit and financial institutions are trying to increase profits, reduce costs, compete with rivals, attract customers and increase productivity. One of the factors that contributes to the implementation of these strategies is the optimum locations of branches. LOCATING the new branches of Mehr Eghtesad bank in the region 1 in Tehran city is the aim of this research. Since the focus of service centers such as banks is on maximal or full service to customers, among the all the covering models, Maximal Covering Location model is chosen as the best option to locate the new BANK BRANCHES. To this end, related literature about LOCATING BANK BRANCHES, Geographical Information system (GIS) and maximal covering location problem (MCLP) examined. Then, through library Studies and interviewing with managers and experts, the researcher chose effective criteria and sub criteria for LOCATING BANK BRANCHES. The weights of criteria and sub criteria were determined through filling the questionnaires by managers. GIS used to extract some input data for the model and weighted maximal covering model (MCLM) with partial covering used to choose the best locations. Mathematical programming model formulated with 363 binary variables, 122 constraints, 121 demand areas, 121 potential points, the 1000 m buffer, a=0.75, b=50%, q=2 and s= 8 & 30 branches (with two different scenarios) and solved with GAMS optimization software. It is clear that by solving the first scenario, eight suitable locations and second scenario thirty suitable locations to open new branches will be generated.

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APA: Copy

MOHAGHAR, ALI, ARYAEE, SARA, HEIDARY, JALIL, & TOOMANIAN, ARA. (2018). USING WEIGHTED MAXIMAL COVERING MODEL WITH PARTIAL COVERAGE AND GEOGRAPHICAL INFORMATION SYSTEMS FOR LOCATING BANK BRANCHES. JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES, 15(47 ), 1-22. SID. https://sid.ir/paper/213211/en

Vancouver: Copy

MOHAGHAR ALI, ARYAEE SARA, HEIDARY JALIL, TOOMANIAN ARA. USING WEIGHTED MAXIMAL COVERING MODEL WITH PARTIAL COVERAGE AND GEOGRAPHICAL INFORMATION SYSTEMS FOR LOCATING BANK BRANCHES. JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES[Internet]. 2018;15(47 ):1-22. Available from: https://sid.ir/paper/213211/en

IEEE: Copy

ALI MOHAGHAR, SARA ARYAEE, JALIL HEIDARY, and ARA TOOMANIAN, “USING WEIGHTED MAXIMAL COVERING MODEL WITH PARTIAL COVERAGE AND GEOGRAPHICAL INFORMATION SYSTEMS FOR LOCATING BANK BRANCHES,” JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES, vol. 15, no. 47 , pp. 1–22, 2018, [Online]. Available: https://sid.ir/paper/213211/en

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