An evolutionary algorithm approach to designing of precast-prestressed concrete road bridges with steel fiber-reinforcement

Abstract

This paper describes a methodology to optimize CO2 emissions and the influence of steel fiberreinforcement when designing precast-prestressed concrete road bridges with a double U-shape cross-section. A hybrid evolutionary algorithm (EA) combining a genetic algorithm (GA) with variabledepth neighborhood search (VDNS) is applied to two objective functions: the embedded CO2 emissions and the economic cost of these structures. A span length of 30m and a deck width of 12m were considered. The problem involved 41 discrete design variables. The module computed the objective functions of a solution and checked all the relevant limit states. The application of the algorithm requires the initial calibration. Each heuristic is run nine times so as to obtain statistical information about the minimum, average and deviation of the results. Finally, solutions and run times indicate that heuristic optimization is a forthcoming option for the design of real-life prestressed structures.