Design optimization of precast-prestressed concrete road bridges with steel fiber-reinforcement by a hybrid evolutionary algorithm

Abstract

In this paper, the influence of steel fiber-reinforcement when designing precast-prestressed concrete (PPC) road bridges with a double U-shape cross-section is studied through heuristic optimization. A hybrid evolutionary algorithm (EA) combining a genetic algorithm (GA) with variable-depth neighborhood search (VDNS) is formulated to minimize the economic cost and CO2 emissions, while imposing constraints on all the relevant limit states. The case study proposed is a 30-m span-length with a deck width of 12 m. The problem involved 41 discrete design variables. The algorithm requires the initial calibration. Moreover, the heuristic is run nine times so as to obtain statistical information about the minimum, average and deviation of the results. The evolution of the objective function during the optimization procedure is highlighted. Findings show that heuristic optimization is a forthcoming option for the design of real-life prestressed structures. This paper provides useful knowledge that could offer a better understanding of the steel fiber-reinforcement in U-beam road bridges.