Publication details
City services provision assessment algorithm
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Proceedings |
| Conference | Procedia Computer Science |
| MU Faculty or unit | |
| Citation | |
| Web | https://doi.org/10.1016/j.procs.2022.10.211 |
| Doi | http://dx.doi.org/10.1016/j.procs.2022.10.211 |
| Keywords | Urban studies; City Provision; urban environment; geospatial analysis; mathematical methods; urban economy; urban planning |
| Description | The paper is dedicated to the problem of computational urban science to estimate availability of urban services with limited capacity. The applied side of the problem is related to the need to assess the provision of citizens living in residential buildings in the city with a sufficient number of places of city services, such as kindergartens, schools, clinics, and others. This information is necessary for the qualitative management of the socio-economic and spatial development of the city. The computational complexity of the problem is associated with a great variety of factors that determine the variability of the citizens' preference function when accessing a particular service. It is further complicated by the presence of self-organization processes within this system, which lead to the actual final satisfaction of the citizens' service demand but with significant deviations from the required parameters of service availability established in regulatory documents or the optimal state of the system. Since validation of such models for large cities is difficult or impossible, this requires the development of new computational approaches for assessing the provision of the population with urban services based on the optimal state of the system to improve the efficiency of city management. A proposed algorithm is based on sequential aggregation of the demand from buildings for each service object and redistribution of unserved demand between other services objects with free capacity. This approach avoids high computational complexity which arises when using nonlinear programming to calculate buildings' provision of services in large cities. The article presents the algorithm for calculating the provision of the population and demonstrates its application on the data of the city of St. Petersburg. |