The objective of this research is to develop computer models for integrated design of steel structures using several emerging computer technologies. They include object-oriented programming (OOP), genetic algorithms, neural network computing, and concurrent processing. The research includes development of a) a blackboard architecture for integrated design of steel structures using the OOP paradigm, b) an object-oriented database management system using an enhanced entity relationship model for managing a multitude of input, intermediate, and output data encountered in integrated design of steel structures, c) an object-oriented version management model based on the parallel version graph, d) an augmented Lagrangian genetic algorithm for detailed design of steel structures, e) an adaptive conjugate gradient integrated design machine learning algorithm for training of multilayer feedforward neural networks, f) a hybrid learning algorithm by integrating genetic algorithm with error backpropagation multilayer neural networks, g) concurrent algorithms for integrated/optimum design of large steel structures such as highrise buildings using the multiprocessing capabilities of shared memory machines (Cray YMP 8/864) and distributed multicomputers (transputers), and h) concurrent algorithms for the hybrid neural networks/genetic algorithm.
