DfMA-oriented design optimization for steel reinforcement using BIM and hybrid metaheuristic algorithms

Abstract

Steel reinforcement (also referred to as rebar) design plays an important role in reinforced concrete (RC) structures in terms of strength requirements, cost and buildability. Currently, rebar design is performed at the individual member level with few considerations of the interference between different intersecting members, leading to potential clashes and buildability issues. Design for Manufacture and Assembly (DfMA) is a cutting-edge technology concept that improves the design for higher buildability by incorporating knowledge from downstream manufacture and assembly activities into the early design phase. This paper presents an innovative DfMA-oriented approach for rebar design optimization with Building Information Modeling (BIM) and a hybrid metaheuristic algorithm. Firstly, activities related to the manufacture and assembly of rebar are identified to apply DfMA principles, followed by the proposed BIM-based optimization framework. Secondly, multi-objective cost design formulation including both the material cost and the installation cost is proposed, incorporating the design code requirements and DfMA considerations. Following this, key modules for implementation are presented including the rebar layout searching, the hybrid genetic algorithm incorporated with Hooke and Jeeves’s method for optimization and rebar clash avoidance. The illustrative example shows that the proposed approach can generate a series of practical rebar layouts, and a trade-off between the material cost and installation cost is found, which means excessive emphasis on minimizing one of them will lead to the rise of the other.