Accelerated optimization method for low-embodied energy concrete box-girder bridge design

Abstract

Structural optimization is normally carried out by means of conventional heuristic optimization due to the complexity of the structural problems. However, the conventional heuristic optimization still consumes a large amount of time. The use of metamodels helps to reduce the computational cost of the optimization and, along these lines, kriging-based heuristic optimization is presented as an alternative to carry out an accelerated optimization of complex problems. In this work, conventional heuristic optimization and kriging-based heuristic optimization will be applied to reach the optimal solution of a continuous box-girder pedestrian bridge of three spans with a low embodied energy. For this purpose, different penalizations and different initial sample sizes will be studied and compared. This work shows that kriging-based heuristic optimization provides results close to those of conventional heuristic optimization using less time. For the sample size of 50, the best solution differs about 2.54% compared to the conventional heuristic optimization, and reduces the computational cost by 99.06%. Therefore, the use of a kriging model in structural design problems offers a new means of solving certain structural problems that require a very high computational cost and reduces the difficulty of other problems.