A surrogate merit function developed for structural weight optimization problems

Abstract In this paper, a surrogate merit function (SMF) is proposed to be evaluated instead of the traditional functions (i.e., penalized weight structure). The standard format conventional needs several expensive trial-and-error tuning processes enhance optimization convergence quality, retuning for different structural model configurations, and final manual local search in case converges infeasible vicinity global optimum. However, on other hand, SMF has no tunning factor but shows statistically stable performance models, directly outstanding feasible points, superior advantages such as reduced required iterations achieve convergence. words, new no-hassle one due its brilliant user-friendly application robust numerical results. might revolutionary step commercializing design real-world construction market.