Journal of Computational Physics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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Ai Application Programming (Charles River Media Programming)
Ai Application Programming (Charles River Media Programming)
Design of reinforced concrete bridge frames by heuristic optimization
Advances in Engineering Software
Optimum detailed design of reinforced concrete continuous beams using Genetic Algorithms
Computers and Structures
Design of prestressed concrete flat slab using modern heuristic optimization techniques
Expert Systems with Applications: An International Journal
Optimum design of prestressed concrete beams using constrained differential evolution algorithm
Structural and Multidisciplinary Optimization
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This paper deals with the economic optimization of prestressed concrete precast pedestrian bridges typically used in public works construction. These bridges are made of a precast concrete beam that integrates an upper reinforced concrete slab for the pedestrian traffic. The beam has a U-shape cross-section. Typical span lengths range from 20 to 40m and the width ranges from 3.00 to 6.00m. The study shows the efficiency of heuristic optimization by the simulated annealing (SA) and the threshold accepting (TA) algorithms. The evaluation of solutions follows the Spanish code for structural concrete. Stress resultants and envelopes of these structures are computed by direct calculation. Design loads are in accordance to the national IAP code for road bridges. The algorithms are applied to a typical pedestrian bridge of 40m of span length and 6.00m of width. This example has 59 discrete design variables for the geometry of the beam and the slab, materials in the two elements and active and passive reinforcement. The evaluation module includes the limit states that are commonly checked in design: flexure, shear, deflections, etc. The application of the SA and TA algorithms requires the calibration of the initial temperature and threshold, the number of variables modified in each iteration, the length of the Markov chains and the reducing coefficient. Each heuristic is run nine times so as to obtain statistical information about the minimum, average and deviation of the results. Best result has a cost of 38,317@? for the SA algorithm and 38,713@? for the TA algorithm. Finally, solutions and run times indicate that heuristic optimization is a forthcoming option for the design of real prestressed structures.