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Volume 35, Issue 4 (2020)
GeoRes 2020, 35(4): 307-316 |
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Received: 2020/06/27 | Accepted: 2020/09/2 | Published: 2020/09/6
Received: 2020/06/27 | Accepted: 2020/09/2 | Published: 2020/09/6
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Fazel Torshizi D, Naji-Azimi Z, Kazemi M. Application of Dynamic Locating in long-term Urban Management Planning; the Case Study of Counters Offices of Civil Registration Organization. GeoRes 2020; 35 (4) :307-316
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1- Department of Management, Faculty of Economics and Business Administration, Ferdowsi University of Mashhad, Mashhad, Iran
2- Department of Management, Faculty of Economics and Business Administration, Ferdowsi University of Mashhad, Mashhad, Iran, Department of Management, Faculty of Economics and Business Administration Ferdowsi University of Mashhad, Mashhad, Iran.
2- Department of Management, Faculty of Economics and Business Administration, Ferdowsi University of Mashhad, Mashhad, Iran, Department of Management, Faculty of Economics and Business Administration Ferdowsi University of Mashhad, Mashhad, Iran.
Abstract (2256 Views)
Aims: Improving spatial access to public services is one of the effective tasks of urban management to develop urban living standards which provides justly facilitating and benefiting of received services for citizens. The aim of this study was to apply the dynamic locating of public services centers in long-term urban management planning.
Methodology: In this applied descriptive research, at first the studied conditions were defined in terms of decision variables, parameters, objective function and limitations by reviewing the research background and experts' opinions. Then the data were collected using databases and expert opinions and finally, mathematical modeling of dynamic locating was performed to maximize the desirability of selecting the counters offices of Civil Registration in Mashhad and the model was solved by the CPLEX solver with the branch and cut algorithm.
Findings: While identifying the indicators of desirability of candidate points, the location of offices in urban areas, the time of reopening and closing, and relevant time period were determined. Activity timing and locating offices, covering 80% of the population and suitable geographical distribution with 39 offices were performed, and optimal value of the objective function was achieved in terms of the indicators considered by the stakeholders and maximum desirability.
Conclusion: Due to the low performance of static models, demographic changes and demand in the field of urban management, a dynamic model was used to solve this problem to provide a more accurate picture of the time of office creation in each area, the ability to select offices with appropriate reliability for activity. And allocating the customers of every region per period to the best location in terms of providing stakeholder indicators.
Methodology: In this applied descriptive research, at first the studied conditions were defined in terms of decision variables, parameters, objective function and limitations by reviewing the research background and experts' opinions. Then the data were collected using databases and expert opinions and finally, mathematical modeling of dynamic locating was performed to maximize the desirability of selecting the counters offices of Civil Registration in Mashhad and the model was solved by the CPLEX solver with the branch and cut algorithm.
Findings: While identifying the indicators of desirability of candidate points, the location of offices in urban areas, the time of reopening and closing, and relevant time period were determined. Activity timing and locating offices, covering 80% of the population and suitable geographical distribution with 39 offices were performed, and optimal value of the objective function was achieved in terms of the indicators considered by the stakeholders and maximum desirability.
Conclusion: Due to the low performance of static models, demographic changes and demand in the field of urban management, a dynamic model was used to solve this problem to provide a more accurate picture of the time of office creation in each area, the ability to select offices with appropriate reliability for activity. And allocating the customers of every region per period to the best location in terms of providing stakeholder indicators.
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English Expanded Abstract [HTML 16 KB] (17 Download)
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