This article aims to describe a methodology to design RC building frames based on a multiobjective simulated annealing (MOSA) algorithm applied to four objective functions, namely, the economic cost, the constructability, the environmental impact, and the overall safety of RC framed structures. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a symmetrical building frame with two bays and four floors. This example has 77 design variables. Pareto results of the MOSA algorithm indicate that more practical, more constructable, more sustainable, and safer solutions than the lowest cost solution are available at a cost increment acceptable in practice. Results N s -SMOSA1 and N s -SMOSA2 of the cost versus constructability Pareto front are finally recommended because they are especially good in terms of cost, constructability, and environmental impact. Further, the methodology proposed will help structural engineers to enhance their designs of building frames.
This paper describes one approach to a methodology to design reinforced concrete cantilever retaining walls for road construction, using a hybrid multistart optimization strategic method based on a variable neighborhood search threshold acceptance strategy (VNS-MTAR) algorithm. This algorithm is applied to two objective functions: the embedded CO2 emissions and the economic cost of reinforced concrete walls at different stages of materials production, transportation and construction. The problem involved 20 design variables: four geometric variables (thickness of the stem and the base slab, as well as the toe and heel lengths), four material types, and 12 variables for the reinforcement set-up. Results first indicate that embedded emissions and cost are closely related, and that more environmentally-friendly solutions than the lowest cost solution are available at a cost increment of less than 1.28%. The analysis also indicated that reducing costs by one euro could save up to 2.28% kg in CO2 emissions.Finally, the cost-optimized walls require about 4.8% more concrete than the best environmental ones, which need 1.9% more steel.
ElsevierMartí Albiñana, JV.; Gonzalez Vidosa, F.; Yepes Piqueras, V.; Alcalá González, J. (2013
AbstractThis paper describes one approach to the analysis and design of prestressed concrete precast road bridges, with double U-shaped cross-section and isostatic spans. The procedure used to solve the combinatorial problem is a variant of simulated annealing with a neighborhood move based on the mutation operator from the genetic algorithms (SAMO). This algorithm is applied to the economic cost of these structures at different stages of manufacturing, transportation and construction. The problem involved 59 discrete design variables for the geometry of the beam and the slab, materials in the two elements, as well as active and passive reinforcement. The parametric study showed a good correlation for the cost, geometric and reinforcement characteristics with the span length, which can be useful for the day-to-day design of PC precast bridges. A cost sensitivity analysis first indicates that a maximum 20% rise in steel costs leads to an 11.82% increase in the cost, while a 20% rise in concrete costs increases the cost up to 4.20%, namely 2.8 times less. The analysis also indicated that the characteristics of the cost-optimized bridges are somewhat influenced by different economic scenarios for steel and concrete costs. Finally, there is a growth in the volume of concrete when the steel cost rises; surprisingly, the variation in the volume of concrete is almost insensitive to its rising price.
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