en Optimal design Optimal design پژوهشي Research <span style="font-size:11.5pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">In this study, the Improved Material Generation Algorithm (IMGA) is proposed to optimize the shape and size of structures. The original Material Generation Algorithm (MGA) introduced an optimization model inspired by the high-level and fundamental characteristics of material chemistry, particularly the configuration of compounds and chemical reactions for generating new materials. MGA uses a Gaussian normal distribution to produce new combinations. To enhance MGA for adapting truss structures, a new technique called Random Chaotic (RC) is proposed. RC increases the speed of convergence and helps escape local optima. To validate the proposed method, several truss structures, including a 37-bar truss bridge, a 52-bar dome, a 72-bar truss, a 120-bar dome, and a 200-bar planar structure, are optimized under natural frequency constraints. Optimizing the shape and size of structures under natural frequency constraints is a significant challenge due to its complexity. Choosing the frequency as a constraint prevents resonance in the structure, which can lead to large deformations and structural failure. Reducing the vibration amplitude of the structure decreases tension and deflection. Consequently, the weight of the structure can be minimized while keeping the frequencies within the permissible range. To demonstrate the superiority of IMGA, its results are compared with those of other state-of-the-art metaheuristic methods. The results show that IMGA significantly improves both exploitation and exploration.</span></span></span> Dynamic Constraint, Metaheuristic Algorithms, Truss Optimization, Soft Computing, Natural Frequency Constraints 15 37 http://ijoce.iust.ac.ir/browse.php?a_code=A-10-6538-1&slc_lang=en&sid=1 V. Goodarzimehr v.goodarzimehr@scu.ac.ir 180031947532846002806 180031947532846002806 Yes Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz, Ahvaz, Iran N. Fanaie fanaie@kntu.ac.ir 180031947532846002807 180031947532846002807 No Department of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran S. Talatahari siamak.talat@gmail.com 180031947532846002808 180031947532846002808 No School of Computing, Macquarie University, Sydney, Australia