Rezumat/Abstract. Rapid population growth and climate change pose great challenges to neighborhood design. Computational urban planning can aid designers in developing sustainable master plans. The objective of this paper is to conduct a systematic review of recent scientific models that optimized urban forms to achieve environmental performance. The methodology thus includes an analysis of twenty recent models to understand the current trend of utilizing parametric design for urban optimization. Frequency analysis, cluster analysis, and comparative analysis are included in the research. The study reveals a gap in optimizing environmental performance and generative design on an urban scale, as thirty-five percent of the models did not optimize urban design and layout parameters. Nevertheless, most of the models prioritized thermal comfort and energy efficiency as primary environmental objectives. The major limitation is that ninety percent of the models focus on hypothetical building forms rather than real urban morphology. This research proposes the potential of parametric design for creating environmentally sustainable cities while highlighting areas for future development in the field. This study's findings will benefit urban planners in understanding the current trends, tools, and limitations of parametric optimization and will guide a scientific approach to its application.

Cuvinte cheie/Key words: computational urban planning, neighborhood design, grasshopper, generative design, multi-objective optimization, thermal comfort

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