Fernando González-Vidosa

Multiobjective Optimization of Concrete Frames by Simulated Annealing

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.

Design of reinforced concrete bridge frames by heuristic optimization

This paper deals with the economic optimization of reinforced concrete box frames used in road construction. It shows the efficiency of four heuristic algorithms applied to a problem of 50 design variables. Heuristic methods used are the random walk and the descent local search. The metaheuristic methods are the threshold accepting and the simulated annealing. The four methods have been applied to the same frame of 13 m of horizontal span. The comparison of the four heuristic algorithms leads to the conclusion that the proposed threshold accepting is more efficient, since it improves cost results of the random walk and descent local search by 7.5% and 1.4%, respectively, while improving deviation of random results of the simulated annealing. Finally, the inclusion of the deflections and fatigue limit states appears to be crucial, since their ignorance leads to 3.9% more economic but unsafe results.

Design of reinforced concrete road vaults by heuristic optimization

This paper aims at the automatic design and cost minimization of reinforced concrete vaults used in road construction. This paper presents three heuristic optimization methods: the multi-start global best descent local search (MGB), the meta-simulated annealing (SA) and the meta-threshold acceptance (TA). Penalty functions are used for unfeasible solutions. The structure is defined by 49 discrete design variables and the objective function is the cost of the structure. All methods are applied to a vault of 12.40m of horizontal free span, 3.00m of vertical height of the lateral walls and 1.00m of earth cover. This paper presents two original moves of neighborhood search and an algorithm for the calibration of SA-TA algorithms. The MGB algorithm appears to be more efficient than the SA and the TA algorithms in terms of mean results. However, the SA outperforms MGB and TA in terms of best results. The optimization method indicates savings of about 10% with respect to a traditional design.

Memetic Algorithm Approach to Designing Precast-Prestressed Concrete Road Bridges with Steel Fiber Reinforcement

AbstractThis paper describes the influence of steel fiber-reinforcement on the design of cost-optimized, prestressed concrete, precast road bridges, with a double U-shaped crosssection and isostatic spans. A memetic algorithm with variable-depth neighborhood search is applied to the economic cost of these structures at different stages of manufacturing, transportation, and construction. The problem involved 41 discrete design variables for the geometry of the beam and the slab, materials in the two elements, active and passive reinforcement, as well as residual flexural tensile strength corresponding to the fibers. The use of fibers decreases the mean weight of the beam by 1.72% and reduces the number of strands an average of 3.59%, but it increases the passive reinforcement by 8.71% on average, respectively. Finally, despite the higher cost of the fibers, their use is economically feasible since the average relative difference in cost is less than 0.19%.

Optimization of Reinforced Concrete Structures by Simulated Annealing

Early attempts of optimised structural designs go back to the 1600s, when Leonardo da Vinci and Galileo conducted tests of models and full-scale structures [1]. A 1994`s review of structural optimization can be found in the study by Cohn and Dinovitzer [2], who pointed out that there was a gap between theoretical studies and the practical application in practice. They also noted the short number of studies that concentrated on concrete structures. A review of structural concrete optimization can be found in the 1998`s study by Sarma and Adeli [3]. The methods of structural optimization may be classified into two broad groups: exact methods and heuristic methods. The exact methods are the traditional approach. They are based on the calculation of optimal solutions following iterative techniques of linear programming [4,5]. The second main group comprises the heuristic methods, whose recent development is linked to the evolution of artificial intelligence procedures. This group includes a broad number of search algorithms [6-9], such as genetic algorithms, simulated annealing, threshold accepting, tabu search, ant colonies, etc. These methods have been successful in areas different to structural engineering [10]. They consist of simple algorithms, but require a great computational effort, since they include a large number of iterations in which the objective function is evaluated and the structural restrictions are checked. Among the first studies of heuristic optimization applied to structures, the contributions of Jenkins [11] and of Rajeev and Krishnamoorthy [12] in the early 1990s are to be mentioned. Both authors applied genetic algorithms to the optimization of the weight of steel structures. As regards RC structures, early applications in 1997 include the work of Coello et al [13], who applied genetic algorithms to the economic optimization of RC beams. Recently, there has been a number of RC applications [14-16], which optimize RC beams and building frames by genetic algorithms. Also recently, our research group has applied simulated annealing and threshold acceptance to the optimization of walls, frame bridges and building frames [17-20]. However, despite advances on structural concrete optimization, present design-office practice of concrete structures is much conditioned by the experience of structural engineers. Most procedures are based on the adoption of cross-section dimensions and material grades based on sanctioned common practice. Once the structure is defined, it follows the analysis of stress resultants and the computation of passive and active O pe n A cc es s D at ab as e w w w .ite ch on lin e. co m

Diseño automático de tableros óptimos de puentes de carretera de vigas artesa prefabricadas mediante algoritmos meméticos híbridosAutomated design of prestressed concrete precast road bridges with hybrid memetic algorithms

This paper deals with the minimum cost automatic design of precast bridge decks made of U-beams and an upper slab. It uses a hybrid memetic algorithm that combines the population search of solutions by genetic algorithms and a search by variable neighborhood. This algorithm is applied to a bridge made of two isostatic U-beams of 20-40 m of span and a width of 12 m. This example has 40 discrete variables. The evaluation module takes into account the service and ultimate limit states usually considered for these structures, i.e. flexure, shear, torsion, cracking, deflections, etc. The use of the memetic algorithm requires its previous calibration. Each of the heuristics is run 12 times, obtaining information about the minimum and average values, as well as the scatter. The parametric study showed a good correlation for the cost, the number of strands and the steel and concrete quantities with the span length. Savings have been found between 8 and 50% compared to other structures really executed. The presented procedure allows the practical application to the real design and its adaptation to the precast process.

Diseño automático de tableros óptimos de puentes de carretera de vigas artesa prefabricadas mediante algoritmos meméticos híbridos

This paper deals with the minimum cost automatic design of precast bridge decks made of U-beams and an upper slab. It uses a hybrid memetic algorithm that combines the population search of solutions by genetic algorithms and a search by variable neighborhood. This algorithm is applied to a bridge made of two isostatic U-beams of 20-40 m of span and a width of 12 m. This example has 40 discrete variables. The evaluation module takes into account the service and ultimate limit states usually considered for these structures, i.e. flexure, shear, torsion, cracking, deflections, etc. The use of the memetic algorithm requires its previous calibration. Each of the heuristics is run 12 times, obtaining information about the minimum and average values, as well as the scatter. The parametric study showed a good correlation for the cost, the number of strands and the steel and concrete quantities with the span length. Savings have been found between 8 and 50% compared to other structures really executed. The presented procedure allows the practical application to the real design and its adaptation to the precast process.

Automated design of prestressed concrete precast road bridges with hybrid memetic algorithms

This paper deals with the minimum cost automatic design of precast bridge decks made of U-beams and an upper slab. It uses a hybrid memetic algorithm that combines the population search of solutions by genetic algorithms and a search by variable neighborhood. This algorithm is applied to a bridge made of two isostatic U-beams of 20-40 m of span and a width of 12 m. This example has 40 discrete variables. The evaluation module takes into account the service and ultimate limit states usually considered for these structures, i.e. flexure, shear, torsion, cracking, deflections, etc. The use of the memetic algorithm requires its previous calibration. Each of the heuristics is run 12 times, obtaining information about the minimum and average values, as well as the scatter. The parametric study showed a good correlation for the cost, the number of strands and the steel and concrete quantities with the span length. Savings have been found between 8 and 50% compared to other structures really executed. The presented procedure allows the practical application to the real design and its adaptation to the precast process.