Early-stage architectural design requires balancing multiple and often conflicting objectives such as structural stability, high environmental performance, material efficiency, low cost, and carbon footprint. While computational tools and search-based optimization methods—particularly Genetic Algorithms—have advanced the capacity to evaluate large design spaces, many of these methods remain difficult to use. They often require text-based coding, rely on rigid workflows, and restrict designer interaction to the beginning or end of the optimization process. As a result, the potential for continuous feedback, qualitative assessment, and adaptive reformulation during the design process remains underexplored.

This paper presents Morpho, a multi-objective, designer-in-the-loop design exploration framework implemented as an open-access Grasshopper (GH) plugin. Built on a Genetic Algorithm, Morpho introduces an interactive workflow that supports both quantitative and qualitative evaluation of design alternatives. Its core features include: (1) seamless integration with diverse GH-based simulation tools; (2) dynamic reformulation of objectives and constraints during runtime; (3) continuous visual feedback through real-time data visualization and image capture; (4) a non-destructive population database that preserves all generated solutions for re-evaluation; and (5) prioritizing visual programming instead of text-based scripting. Together, these features allow designers to explore, assess, and refine design solutions without restarting the optimization process or losing prior data.

In this paper, a case study on a folded-plate CLT toroidal dome examines Morpho’s capability to manage both divergent and convergent search phases while evaluating structural performance, life cycle assessment, and fabrication waste. The study highlights how Morpho enables designers to incorporate both objective metrics and subjective preferences within the same exploration workflow.

The findings position Morpho as an advancement in interactive, performance-informed design—bridging the gap between automated optimization and creative authorship. By lowering technical barriers, integrating multiple performance domains, and emphasizing designer agency, Morpho contributes a practical and adaptable framework for early-stage architectural decision-making.

Post-disaster housing demands solutions that balance speed, cost, and environmental responsibility; however, the long-term sustainability of Modular Construction (MC) remains insufficiently quantified. This study addresses this gap by integrating simulation-based Life Cycle Assessment (LCA), parametric energy modeling, and multi-objective design optimization to evaluate the environmental performance of modular housing systems used in disaster recovery. Using a workflow that integrates Parametric Environmental Simulation Tools such as Rhino-Grasshopper, Ladybug/Honeybee, and BIM-based LCA, the research assesses embodied carbon, material efficiency, operational energy use, and construction duration for modular units compared with conventional construction. The findings show that MC can substantially reduce embodied carbon and material demand relative to traditional building methods, with reductions generally ranging from 20% to 35%, depending on unit type and material configuration. Multi-objective optimization (MOO) further identifies modular design options that balance rapid assembly with improved environmental performance, revealing that optimized modules can achieve lower emissions while maintaining competitive construction timelines. Energy simulations indicate that modular units perform comparably to, or in some cases better than, conventional buildings in operational energy use, particularly when envelope parameters are adjusted to reflect local climate conditions. The results also highlight key trade-offs common in post-disaster reconstruction, such as the tension between rapid deployment and long-term carbon performance, or between standardized modular design and the need for climate-responsive adaptation. These findings align with broader net-zero debates that emphasize the need to reconcile speed, cost, and carbon reductions within urgent reconstruction timelines. By integrating the Parametric Environmental Simulation Toolkit into a unified workflow, this study provides a replicable framework that supports evidence-based decision-making for designers, policymakers, and emergency response agencies seeking low-carbon, climate-adaptive housing solutions.

The construction industry has traditionally been slow to adopt new technologies, largely due to the scale of projects and the challenges of integrating emerging systems into established workflows. Rather than rethinking the design process from the ground up, many conventional approaches apply new technologies to existing design paradigms. In structural design, beam members have been a central focus of optimization efforts; however, most studies address isolated parameters, such as material efficiency, structural performance, or fabrication constraints, without unifying them within a comprehensive multi-objective optimization (MOO) framework.

This study introduces a metric-based design method grounded in a MOO framework aimed at optimizing concrete beam members. Unlike prior work, the proposed approach incorporates equations that governs the geometry of the beam, generated through the use of flexible formwork. These equations serve as the core design variable in the optimization process, enabling a continuous and parameterized exploration of beam shapes that balance multiple objectives. The method targets the simultaneous minimization of material use and fabrication complexity while maximizing structural efficiency.

By providing a direct solution that informs formwork design and integrates into the MOO model, this research offers a practical and adaptable tool for construction professionals. The approach lowers the barrier to adoption by emphasizing simplicity and ease of implementation, supporting the Architecture, Engineering, and Construction (AEC) industry’s broader transition toward more sustainable, high-performance, and digitally integrated design practices.