Application of Genetic Algorithm for Optimal Design of Portal Frame Structures

This study developed and applied a MATLAB-based Genetic Algorithm (GA) program for the optimal design of steel portal frames with the aim of minimising cross-sectional area, weight, and cost. A single-span pitched-roof frame of 30 m span, 7 m eave height, and 3.5 m overheight was analysed, with variations in frame spacing from 6 m to 7.5 m, using S275 steel and BS 5950 design provisions. The GA optimisation consistently converged to efficient solutions, achieving 4–13 % cost savings and up to 10 % weight reduction compared with the empirical method. Results further showed that the column plastic modulus was approximately 50 % greater than that of the rafter, rafter depth was about span/55, and purlin depth was roughly one-quarter of the rafter depth. Although minor variations occurred due to stochastic algorithm behaviour, all runs produced results within the same performance bounds. The findings confirm the reliability of the developed GA framework as a practical and computationally efficient tool for designing cost-effective and structurally sound steel portal frames.

Genetic algorithm, optimisation, portal frame, steel structures

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