Key points are not available for this paper at this time.
Abstract In this article size/geometry optimization of trusses is performed using the force method and genetic algorithm. A large number of design variables consisting of cross‐sectional areas and nodal coordinates are involved in such an optimization, and due to a large number of constraints, the dimensions of the design space are often numerous and in the case of discrete values for cross sections usually discontinuous. In order to avoid local optima, modified genetic algorithms are developed. Furthermore, the force method is employed to improve the speed of the optimization. In the first phase of the described method, the initial geometry of the truss is fixed and near optimum ranges for the cross‐section areas are obtained using the relationships from the force method. In the second phase, the geometry of the structure is altered with the aim of designing lower‐weight structures. Within the Genetic Algorithm a new dynamic penalty function is defined and a modified process of reproduction is presented. A contraction process is also employed for the design space using shorter substrings for the design variables.
Kaveh et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: