Investigating bound handling schemes and parameter settings for the interior search algorithm to solve truss problems

The interior search algorithm (ISA) is an optimization algorithm inspired by esthetic techniques used for interior design and decoration. The algorithm has only one parameter, controlled by θ, and uses an evolutionary boundary constraint handling (BCH) strategy to keep itself within an admissible solution space while approaching the optimum. We apply the ISA to find optimal weight design of truss structures with frequency constraints. Sensitivity of the ISA's performance to the θ parameter and the BCH strategy is investigated by considering different values of θ and BCH techniques. This is the first study in the literature on the sensitivity of truss optimization problems to various BCH approaches. Moreover, we also study the impact of different BCH methods on diversification and intensification. Through extensive numerical simulations, we identified the best BCH methods that provide consistently better results for all truss problems studied, and obtained a range of θ that maximizes the ISA's performance for all problem classes studied. However, results also recommend further fine-tuning of parameter settings for specific case studies to obtain the best results.