Development of Robust Optimization Algorithms Based on Adaptive Biological Growth Method
Many shape and topology optimization methods have been inspired from the nature. In this paper، two different optimization algorithms based on the adaptive biological growth (ABG) have been applied to some structural elements. The first algorithm is developed for the shape optimization and is applied to a plate with a central hole as well as a fillet plate. The second algorithm is the soft kill option (SKO) that is applied to a cone cantilever beam and a beam with variable cross section where the optimum topology of them are sought. The results show that the fatigue life of the plate with a central hole is increased by 40 times. Also، the maximum normalized first principle stress is 6% lower and finally، the volume of the optimum structure is less than those obtained by other researchers.
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