Computational Urban Planning

Sometimes mundane interactions can lead to interesting ideas. I was talking to a friend about what could be a worthwhile research problem. We thought that how nice it would be to be able to design better cities, towns, and villages. Most of our rural infrastructure is unplanned. And most of our cities are poorly designed. If we could plan our future cities, towns and villages in a better way, quality of life and the human condition could be improved tremendously. In this article, I am sharing online resources that are relevant for computational urban/town planning.

Computational Approaches for Urban Environments | Marco Helbich | Springer

This book aims to promote the synergistic usage of advanced computational methodologies in close relationship to geospatial information across cities of…

Application of Genetic Algorithm to Spatial Distribution in Urban Planning – IEEE Xplore Document

Urban planning is a important part of urban construction, spatial distribution is subordinate to urban planning, it is difficult to obtain a satisfactory s

Application of Advanced Hybrid Genetic Algorithms for Optimal Locations of High School

In this study, an advanced hybrid genetic algorithms is formulated and applied to the optimal location of high schools in a rural area of Bangladesh. The advanced hybrid algorithms consist of genetic

City Planning with a Multiobjective Genetic Algorithm and a Pareto Set Scanner

A genetic algorithm was used to search for optimal future land use and transportation plans for a pair of high-growth cities. Hundreds of thousands of plans were considered. Constraints were imposed t

A linguistic cellular automata simulation approach for sustainable land development in a fast growing region – ScienceDirect

Rapid rural-urban land conversion as a consequence of economic growth has raised serious concerns over sustainable development. There is an urgent need to understand what possible urban scenarios can result from different policies towards land conversions. In many ways, the question resembles the exploration of a self-organising phenomenon which generates macroscopic patterns upon microscopic and local decision-making processes.

PSOSA: An Optimized Particle Swarm Technique for Solving the Urban Planning Problem – IEEE Xplore Document

This paper introduces an optimized particle swarm technique (PSOSA) that uses simulated annealing for optimizing the inertia weight. To study the performan

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CC BY-NC-ND 4.0 Computational Urban Planning by Psyops Prime is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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