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A platform for research: civil engineering, architecture and urbanism
Cost and CO2 emission optimization of precast–prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm
Abstract This paper describes a methodology to optimize cost and CO2 emissions when designing precast–prestressed concrete road bridges with a double U-shape cross-section. To this end, a hybrid glowworm swarm optimization algorithm (SAGSO) is used to combine the synergy effect of the local search with simulated annealing (SA) and the global search with glowworm swarm optimization (GSO). The solution is defined by 40 variables, including the geometry, materials and reinforcement of the beam and the slab. Regarding the material, high strength concrete is used as well as self-compacting concrete in beams. Results provide engineers with useful guidelines to design PC precast bridges. The analysis also revealed that reducing costs by 1 Euro can save up to 1.75kg in CO2 emissions. Finally, the parametric study indicates that optimal solutions in terms of monetary costs have quite a satisfactory environmental outcome and differ only slightly from the best possible environmental solution obtained.
Highlights A methodology to optimize CO2 emissions when designing PC precast road is proposed. A new hybrid glowworm swarm optimization algorithm (SAGSO) is described. Optimal cost solutions have quite a satisfactory environmental outcome when using high strength and self-compacting concrete. The study is adjustable to the constraints and particular needs of realistic projects.
Cost and CO2 emission optimization of precast–prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm
Abstract This paper describes a methodology to optimize cost and CO2 emissions when designing precast–prestressed concrete road bridges with a double U-shape cross-section. To this end, a hybrid glowworm swarm optimization algorithm (SAGSO) is used to combine the synergy effect of the local search with simulated annealing (SA) and the global search with glowworm swarm optimization (GSO). The solution is defined by 40 variables, including the geometry, materials and reinforcement of the beam and the slab. Regarding the material, high strength concrete is used as well as self-compacting concrete in beams. Results provide engineers with useful guidelines to design PC precast bridges. The analysis also revealed that reducing costs by 1 Euro can save up to 1.75kg in CO2 emissions. Finally, the parametric study indicates that optimal solutions in terms of monetary costs have quite a satisfactory environmental outcome and differ only slightly from the best possible environmental solution obtained.
Highlights A methodology to optimize CO2 emissions when designing PC precast road is proposed. A new hybrid glowworm swarm optimization algorithm (SAGSO) is described. Optimal cost solutions have quite a satisfactory environmental outcome when using high strength and self-compacting concrete. The study is adjustable to the constraints and particular needs of realistic projects.
Cost and CO2 emission optimization of precast–prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm
Yepes, Víctor (author) / Martí, José V. (author) / García-Segura, Tatiana (author)
Automation in Construction ; 49 ; 123-134
2014-10-21
12 pages
Article (Journal)
Electronic Resource
English
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