Generative Urbanism — U.S.-Mexico Border Revitalization
2023 · Urban Planning

Generative Urbanism — U.S.-Mexico Border Revitalization

Urban Planning

A territorial-scale generative-urbanism investigation along the U.S.-Mexico border, mapping informal settlements and water-infrastructure scarcity. Combines GIS data with rule-based growth simulations to project alternative urban futures across decades.

Evolutionary optimization for urban revitalization at the U.S.-Mexico border — parametric models where urban form adapts to shifting environmental and programmatic conditions rather than being fixed at design time.

urban grid

This project focuses on utilizing evolutionary optimization algorithms to address urban revitalization challenges at the U.S.-Mexico border. The goal was to design adaptable urban interventions that respond to shifting environmental and programmatic conditions. By leveraging parametric tools like Grasshopper and integrating evolutionary algorithms, the project explores generative design strategies that allow for dynamic form-finding and spatial planning. The workflow involved creating and refining algorithmic models that simulated adaptive urban scenarios — optimizing factors such as spatial organization, programmatic proximity, and accessibility.

Key technical tools included Grasshopper for parametric modeling and evolutionary solvers like Galapagos for multi-criteria optimization. This approach resulted in adaptive design solutions aimed at enhancing urban spaces’ flexibility and resilience in a rapidly changing context.

Approach

  1. Parametric urban model — Grasshopper definition with adjustable block geometry, program mix, accessibility graphs
  2. Objective functions — spatial organization quality, programmatic proximity, accessibility scoring
  3. Evolutionary solver — Galapagos runs multi-criteria optimization over block arrangements
  4. Adaptive scenarios — parameters vary with environmental / programmatic shifts; design responds generatively rather than from fixed plan

evolution 2 evolution 3 evolution 4 evolution 5 evolution 6 evolution 7

Outcomes

  • Demonstrates urban form as evolved-not-authored
  • Multiple optimized layouts surfacing tradeoffs (density vs. accessibility vs. program mix)
  • Positions border revitalization as a generative, adaptive problem rather than a fixed master-plan exercise

Context

Institution: Rice University, undergraduate architecture studio (2021-2024). Role: individual.

  • [[2021-2024-Rice—fiber-based-pavilion]] — parallel Rice parametric research (published at IASS 2024)
  • [[2021-2024-Rice—membrane-form-finding]] — Rice parametric studio work
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