Optimization of the One-Size-Fits-All Layout Problem Based on Preparing Material for Steel Bridges

Abstract

Before the construction of a bridge begins, workers arrange the necessary parts and then cut and process them. The quality of the cutting layout directly affects the material utilization rate and the efficiency of the subsequent processes. During bridge construction, an intelligent part layout can improve work efficiency, save time, and reduce the labor intensity and production costs for the company. In this study, we studied a layout optimization algorithm, focusing on rectangular parts in the material preparation process. A mathematical model for the rectangular layout problem was constructed, and a hybrid genetic whale optimization algorithm is proposed that is a combination of the whale optimization algorithm and the genetic algorithm. Based on the “one size fits all” layout strategy, the materials are divided into strips, which are further divided into stacks, serving as the positioning strategy to determine the positional relationships of the parts. Test cases and actual engineering data were used to compare the layouts generated using different algorithms. The results show that the genetic whale algorithm proposed in this paper results in a high utilization rate and is highly effective.