Modified genetic algorithm for efficient optimization: application to prestressed concrete structural elements

Resumo

Prestressing, whether bonded or non-bonded, has become increasingly attractive as it allows for larger spans, greater architectural flexibility, greater agility in execution and greater durability. All of these advantages are capable of making prestressed concrete structures more economical solutions when associated with an efficient scaffolding system and formwork. The use of prestressed beams combined with ribbed slabs allows the slabs and beams to have the same height, thus favoring the architecture, in addition to facilitating the assembly of formwork and concreting. The designer can appropriately define the dimensions of the beams and slabs, as well as parameters such as the quantity and layout of cables by trial based on experience. However, the use of numerical optimization techniques are tools recognized as appropriate for the search for a structural solution, where design parameters, whether at the level of design (topology), intermediate (shape) or detail (dimension), can be determined such that the solution minimizes a performance measure, for example, cost, which takes into account the cost of materials, the volume of concrete, the weight of passive and active reinforcement, and labor productivity. Given the discrete nature of some variables, genetic algorithms (GA) have been widely used. GAs have control parameters and operators that are, in general, dependent on the problem, requiring calibrations in each case. The objective of this work is to review some optimization models and improve the GA of the BIOS program - developed at the (Computational Mechanics and Visualization Laboratory) LMCV of the Federal University of Ceará (UFC) - investigating new operators, thus aiming at the efficiency of the algorithm for prestressed elements, using a prestressed band beam as a case study. Genetic operators, in particular crossover, will be targets of the study.