Adaptive Urban Planning: A Hybrid Framework for Balanced City Development

TL;DR

This paper introduces a hybrid urban planning framework that combines top-down and bottom-up approaches, using a two-tier system with specialized agents to optimize infrastructure and demographic preferences in rapidly developing cities.

Contribution

The paper presents a novel two-tier hybrid framework integrating deterministic optimization with regional planning agents for balanced urban development.

Findings

Improved urban development balance in case studies.

Enhanced integration of regional preferences with city-wide planning.

Framework validated on real city data from India.

Abstract

Urban planning faces a critical challenge in balancing city-wide infrastructure needs with localized demographic preferences, particularly in rapidly developing regions. Although existing approaches typically focus on top-down optimization or bottom-up community planning, only some frameworks successfully integrate both perspectives. Our methodology employs a two-tier approach: First, a deterministic solver optimizes basic infrastructure requirements in the city region. Second, four specialized planning agents, each representing distinct sub-regions, propose demographic-specific modifications to a master planner. The master planner then evaluates and integrates these suggestions to ensure cohesive urban development. We validate our framework using a newly created dataset comprising detailed region and sub-region maps from three developing cities in India, focusing on areas undergoing rapid urbanization. The results demonstrate that this hybrid approach enables more nuanced urban development while maintaining overall city functionality.