A novel special length rebar order approach based on AI optimization techniques for reduction of rebar cutting waste

Abstract

Reducing the amount of waste material in the construction industry is a crucial goal for sustainability worldwide. Cutting rebars to fit the lengths needed for a building generates significant rebar waste. This study aims to reduce rebar-cutting waste in construction projects. In addition to planning the cut lengths of the standard 12-meter rebar using optimization methods, the study intends to reduce rebar-cutting waste by producing rebars in different lengths based on order frequency. A combination of genetic algorithm, fuzzy logic system, and a new algorithm method optimizes the cutting process, resulting in a significant reduction of rebar waste. Unlike prior studies, this research proposes a unique cutting length order for the rebar list created after optimization, aiming to reduce rebar cutting waste below the optimized level. The results show that the reduction in the amount of rebar waste is satisfactory.