Document Type

Article

Publication Date

12-25-2024

Publication Title

Architecture

Volume

5

Issue

2

First page number:

1

Last page number:

23

Abstract

Multi-objective evolutionary algorithms have long been used by architects to find objective solutions to complex building problems involving trade-offs implicit in sustainable building design. At a larger scale, urban designers have created a variety of tools to improve sustainability in urban-and-larger scale design. However, to date, fewer studies have focused on improving sustainability outcomes at the “in between” scale of the neighborhood and urban site. Existing scholarship on optimization at this scale has tended to take a narrow view of sustainability. We seek to expand the implementation of multi-objective evolutionary algorithms to this sometimes overlooked scale while taking a broad view of sustainability which includes social, environmental, and economic design factors. In doing so, we argue this optimization method is uniquely well suited to help designers balance the sometimes competing demands of multiple axes of sustainability which are applicable to design at this larger-than-building scale. In demonstrating the application of such an algorithm to a hypothetical problem in Chicago, we find the method offers a promising way of narrowing potential design solutions. Finally, we discuss the suitability of the solutions generated, the virtues and shortcomings of the method, and offer areas for future study.

Keywords

sustainability; optimization; urbanization; multi-objective optimization

Disciplines

Environmental Design | Urban, Community and Regional Planning

File Format

pdf

File Size

11650 KB

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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