The present paper describes the adaptation of newly emergent computational strategies in the multidisciplinary design of structural systems. Such systems are characterized by computationally intensive analysis that is inherently coupled, high dimensionality indicated by a large number of design variables and constraints, and a design domain that is not always amenable to traditional search strategies. Solution methods for this class of problems have focussed on strategies that decompose the coupled design problem into smaller subproblems that have weak or no couplings, and that can be solved in an ordered sequence or in parallel. Innovative strategies that combine the use of computational paradigms such as genetic algorithms, neural networks, and rule-based systems, can result in the development of quasi-procedural systems that represent significant enhancements over existing tools. The paper shows how computations performed during optimization can be used to develop a knowledge base which allows for a rational partitioning of the problem domain, a method to account for the coupling that exists between the subproblems, and an ability to develop new rules for the rule-based systems. The validation of these concepts is shown by application to simple multidisciplinary structural design problems.

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