Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Design of prestressed concrete precast pedestrian bridges by heuristic optimization
Advances in Engineering Software
Design of reinforced concrete road vaults by heuristic optimization
Advances in Engineering Software
Optimum design of run-flat tire insert rubber by genetic algorithm
Finite Elements in Analysis and Design
Artificial Bee Colony (ABC) algorithm in the design optimization of RC continuous beams
Structural and Multidisciplinary Optimization
Structural and Multidisciplinary Optimization
Hi-index | 0.00 |
This paper presents the application of Genetic Algorithms for the optimum detailed design of reinforced concrete continuous beams based on Indian Standard specifications. The produced optimum design satisfies the strength, serviceability, ductility, durability and other constraints related to good design and detailing practice. While most of the approaches reported in the literature consider the steel reinforcement as a variable, the cross-sectional dimensions of the beam alone are considered as the variables in the present optimum design model. The areas of longitudinal steel obtained from the design are converted into a least weight detailing of steel reinforcements. This is achieved by generating a database of reinforcement templates containing different available reinforcement bar diameters in a pre-specified pattern, satisfying the user specified bar rules and other bar spacing requirements. The optimum design results are compared with those in the available literature. An example problem is illustrated and the results are presented. It is concluded that the proposed optimum design model yields rational, reliable, economical and practical designs.