A multi-set charged system search for truss optimization with variables of different natures; element grouping

Abstract

Optimization problems may include variables of different natures. In structural optimization for example different variables representing cross-sectional, geometrical, topological and grouping properties of the structure may be present. Having different interpretations, the effects of these variables on the objective function are not alike and their search spaces may represent different characteristics. Thus, it is helpful to take these variables apart and to control each set separately. Based on the above considerations, in this paper a multi set charged system search (MSCSS) is introduced for the element grouping of truss structures in a weight optimization process. The results are compared to those obtained through predefined grouping by different algorithms. The comparisons show the efficiency and the effectiveness of the proposed algorithm. Although this paper only considers size optimization of truss structures where sizing and grouping variables are present and regarded as variables of different natures, the algorithm can be extended to cover the simultaneous shape and size optimization and topology optimization of different types of structures.