The paper describes a quasi-procedural approach for the generation of near-optimal structural topologies. Such an approach is characterized by the use of algorithmic processing to enumerate the design space, and to use this information in a design methodology dominated by heuristic decisions. The paper presents a stagewise decomposition approach, which is thematically similar to dynamic programming, to decompose the given problem into a series of stages (subproblems), and generate a population of trial designs. A genetic algorithm based search is then conducted in a discontinuous space with these designs as seeds, to obtain an optimal design for the problem. The issue of structural stability is addressed by the use of embedded heuristics. A representative structural design problem is used to illustrate the approach.

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