OPTIMIZATION OF SKELETAL STRUCTURES USING IMPROVED GENETIC ALGORITHM BASED ON PROPOSED SAMPLING SEARCH SPACE IDEA

In this article, by Partitioning of designing space, optimization speed is tried to be increased by GA. To this end, designing space search is done in two steps which are global search and local search. To achieve this goal, according to meshing in FEM, firstly, the list of sections is divided to specific subsets. Then, intermediate member of each subset, as representative of subset, is defined in a new list. Optimization process is started based on the new list of sections which includes subset’s representatives (global search). After some specific generations, range of optimum design is indicated for each designing variable. Afterwards, the list of sections is redefined relative to previous step’s result and based on subset of relevant variable. Finally, optimization will be continued based on the new list of sections for each designing variable to complete the generations (local search). In this regard, effect of dimension and number of subset’s members of global and local searches in proposal are investigated by optimization examples of skeletal structures. Results imply on optimization speed enhancement based on proposal in different cases proportional to simple and advanced cases of GA.