Heuristic Techniques for the Design of Steel-Concrete Composite Pedestrian Bridges

Abstract

The objective of this work was to apply heuristic optimization techniques to a steel-concrete composite pedestrian bridge, modeled like a beam on two supports. A program has been developed in Fortran programming language, capable of generating pedestrian bridges, checking them, and evaluating their cost. The following algorithms were implemented: descent local search (DLS), a hybrid simulated annealing with a mutation operator (SAMO2), and a glow-worms swarm optimization (GSO) in two variants. The first one only considers the GSO and the second combines GSO and DLS, applying the DSL heuristic to the best solutions obtained by the GSO. The results were compared according to the lowest cost. The GSO and DLS algorithms combined obtained the best results in terms of cost. Furthermore, a comparison between the CO2 emissions associated with the amount of materials obtained by every heuristic technique and the original design solution were studied. Finally, a parametric study was carried out according to the span length of the pedestrian bridge.