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GENETICALLY OPTIMIZED ARTIFICIAL NEURAL NET\VORK BASED OPTIMUM DESIGN OF SINGLY AND DOUBLY REINFORCED CONCRETE BEAMS

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Optimum design of singly and doubly reinforced beams with uniformly distributed and concentrated load has been done by incorporating actual self weight of beam, parabolic stress block, moment-equilibrium and serviceability constraints besides other constraints. Also, this design expertise has been incorporated into a genetically optimized artificial neural network based on steepest descent, adaptive and resilient back-propagation learning techniques. The initial solution for the optimization procedure has been obtained using limit state design as per IS: 456-2000.

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