Salp Swarm Algorithm for Optimization of Shallow Foundations

In this study, two types of shallow foundations, the isolated and combined footing, are optimized to minimize the construction cost using the Salp Swarm Algorithm (SSA) and the Improved Salp Swarm Algorithm (ISSA). The efficiency of each algorithm for designing shallow foundations is examined through numerical examples of benchmark foundations subjected to uniaxial loads, axial and flexural loads, and axial and flexural loads with dynamic column locations. The results indicate that the ISSA generated lower-cost designs than SSA. However, considering the mean cost values over many applications, the SSA outperformed the ISSA. When applying an additional moment to the column on isolated footing, both algorithms generated designs that increased the final cost by more than 178%. On the other hand, when the column could be relocated on the footing to balance uplift pressure, the final design cost was increased by only 62%. Comparing the best designs and convergence rates, the SSA was more efficient for designing a rectangular combined footing. However, the ISSA produced lower mean, median, and standard deviation values than the SSA. Results indicate the ISSA generated better designs for the trapezoidal combined footing, reducing cost by 2.5% compared to the rectangular footing.