Abstract: In order to improve the calculation efficiency of the discrete truss optimization problem,this paper proposes an improved discrete differential evolution algorithm.The mutation strategies is adaptively selected based on population diversity to balance exploration and convergence capabilities,and the population size is adaptively reduced based on individual differences and population diversity to reduce calculations.Heavier trial individuals are discarded before structural analysis to avoid useless calculations,and the elite selection technique is introduced to solve the problem of unequal numbers of target individuals and trial individuals in the selection phase.On this basis,a discretization method that converts the distance between the values into a probability is proposed to solve the problem of discrete variables. Experimental results show that compared with algorithms such as IGA and DE,this algorithm can greatly reduce the structural analysis times while ensuring the optimal solution quality.
discrete differential evolution algorithm,
adaptive mutation strategy,
adaptive population size,
number of structural analysis,