Two intelligent optimisation algorithms are compared for the design of the most economical 3D steel tower based on the lowest total steel weight. The design loads considered are the dead loads (weight of the structure and cables), wind and ice loads. Since there are many possible combinations to this problem, it's challenging for the designer to guarantee that his design is the most cost-effective (minimum weight). To obtain the optimum design subject to constraints, Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) are used. Intelligent algorithms are very effective for optimising these types of problems as it's possible to obtain the best solution with a minimum number of iterations where many different combinations are possible. These algorithms use the principles of learning from the best solution found at each iteration and try to converge towards the best possible global solution. Each iteration finds an equal or better solution than its predecessor and converges to a near-optimum solution. This work was realized to obtain the lowest weight of a 3D steel tower configuration that meets all the requirements of the CSA-S16 and CSA-S37 standards. After entering the tower geometry and loading conditions, the algorithm optimises the size of the structural elements. All structural elements are designed for strength resistance and deflection limits. The performance of the algorithms will be presented based on robustness, reliability, and convergence speed.
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