Urban-Tissue Optimization through Evolutionary Computation

Abstract

The experiments analyzed in this paper focus their research on the use of Evolutionary Computation (EC) applied to a parametrized urban tissue. Through the application of EC, it is possible to develop a design under a single model that addresses multiple conflicting objectives. The experiments presented are based on Cerdà’s master plan in Barcelona, specifically on the iconic Eixample block which is grouped into a 4 × 4 urban Superblock. The proposal aims to reach the existing high density of the city while reclaiming the block relations proposed by Cerdà’s original plan. Generating and ranking multiple individuals in a population through several generations ensures a flexible solution rather than a single “optimal” one. Final results in the Pareto front show a successful and diverse set of solutions that approximate Cerdà’s and the existing Barcelona’s Eixample states. Further analysis proposes different methodologies and considerations to choose appropriate individuals within the front depending on design requirements.

A grammar-based optimization approach for walkable urban fabrics considering pedestrian accessibility and infrastructure cost

“…At an urban design level, Navarro-Mateu et al (2018) and Makki et al (2019) are among the firsts to implement MOO in the generation of urban fabrics, shedding some light on addressing conflicting objectives at this scale. However, neither work considers a grammar-based approach or walkability criteria.…”

The design of social and cultural orientated urban tissues through evolutionary processes

“…Although this is significant within design, it is even more so within an urban scale, as the process allows for the simultaneous output of geometrically unique morphologies from a single simulation, in which the solutions share similar attributes on a global scale, but differ considerably on the local scale. The work of Balling et al, 15 Makki et al, 16 Koenig, 17 Navarro, 18 Showkatbakhsh 19 and others in the field have demonstrated the above, in which the application of MOEAs are used as the primary approach to solve complex design problems, both in gaining a better understanding of their formulation, as well as achieving results that are driven by quantitatively measurable data sets. Where these studies have thoroughly examined the application of population based evolutionary algorithms to generate urban form, there remains the challenge of selecting viable urban solutions based on the morphological representation of the data outputted by the evolutionary simulation, in which the data set is optimised to allow for the data-driven and comparative visual analysis and selection of the outputted solution set.…”

A Grammar-Based Optimization Approach for Designing Urban Fabrics and Locating Amenities for 15-Minute Cities

“…Their use on the urban scale is still limited compared to architecture due greater complexity and computational requirements. However, many scholars have explored optimization as a tool to discover potentially improved urban designs from several viewpoints [14,15,20,43,44]. In our work, we understand optimization as a resource for finding possibilities or even directions for further exploration and refinement instead of a deterministic approach to choose a single, perfect solution.…”