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District Design Automation

Student: Tigina Mariia

Supervisor: Boris Novikov

Faculty: St. Petersburg School of Physics, Mathematics, and Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2021

The development of a neighbourhood planning project is a critical and complex spatial planning task which consists in finding the optimum location of different urban development objects within the boundaries of a given territory, taking into account all regional constraints. Due to the active development of new territories, the expansion of cities and the increasing complexity of their structure, the question of automating the process of creating territorial plans has become extremely topical. Over the last 10 years, many algorithms for automatic generation and optimization have been developed in related fields, and several automatic design tools such as Grasshopper, KPF, ArcGIS have been implemented. But because of the incompleteness of the proposed optimizations and the regional specificity of these tools, most planning projects are carried out by the urbanists manually, resulting in sub-optimal solutions with high time and financial costs. This work proposes an approach to the implementation of a regional-independent service for the automatic generation of optimum neighbourhood planning projects. It is based on an algorithm for the joint generation and optimization of all planning objects under constraints on the parameters of the project, obtained by adapting, combining and comparing different existing mathematical approaches and algorithms. The tool was tested on real projects in four regions, taking into account their specific parameters, target functions and regulatory constraints. The developed automated solution is not inferior to the manual one and gives an increase in planned tasks by 2-5%, and also speeds up the process of creating a territory planning. Keywords: urban planning automation, drafts generation and optimization, multi-objective constraint optimization, computational geometry.

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