Multi-objective optimization design approach for prefabricated buildings to minimize cost, duration and carbon...

Area of Science:

• Civil Engineering
• Sustainable Construction
• Optimization Algorithms

Background:

• Traditional cast-in-place construction faces challenges in cost, duration, and environmental impact.
• Prefabricated construction offers potential benefits but requires optimized design strategies.
• Balancing cost, time, and carbon emissions is crucial for sustainable building development.

Purpose of the Study:

• To propose a multi-objective optimization design approach for prefabricated building components.
• To minimize cost, construction duration, and carbon emissions simultaneously.
• To utilize the ant colony algorithm for optimizing prefabricated construction.

Main Methods:

• Employing a multi-objective optimization design approach for prefabricated components (columns, beams, slabs, walls, stairs).
• Defining cost, duration, and carbon emissions as objective functions.
• Using construction technologies (cast-in-place vs. prefabricated) as variables and prefabrication rate as constraints.
• Applying the ant colony algorithm to find optimal solutions.

Main Results:

• The optimized prefabricated building design achieved reductions of 0.42% in cost, 19.05% in duration, and 13.49% in carbon emissions compared to cast-in-place construction.
• Sub-target weight and prefabrication rate significantly influence the optimal component combination.
• Maximum reductions of 1.26% in cost, 27.89% in duration, and 18.4% in carbon emissions were observed under varied scenarios.

Conclusions:

• The proposed ant colony algorithm-based approach effectively minimizes cost, duration, and carbon emissions in prefabricated buildings.
• This method provides a viable pathway for transitioning from cast-in-place to prefabricated construction.
• The approach supports sustainable development within the building industry.