Structural optimization, in the classic sense, is the minimization of mass by varying or determining the different design variables. Shape optimization, however, is to maximize the use of materials under the allowable design performances. It plays a significant part in the preliminary design stage and has been considered as the most challenging and economically the most rewarding task in structural design. During the past few years, genetic-based optimization approaches have been applied to many structural design problems with great success. In this paper, a new approach integrating genetic algorithms with fuzzy rule-based system for structural shape optimization is investigated. An automated optimization procedure based upon the proposed approach is developed and used in the least-weight shape design of truss structures, which include their geometry as a design variable to be optimized. The approach uses a fuzzy control strategy to guide the genetic algorithm based search to get the maximum optimization improvement in as few search steps as possible. A representative example is presented to verify the applicability and effectiveness of the proposed approach to structural shape optimization.

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