Symbiotic organisms search with the feasibility-based rules for constrained engineering design optimization

During the past decades, metaheuristic algorithms have been utilized to deal with constrained optimization with a high degree of success. Recently, symbiotic organisms search (SOS), a promising and new metaheuristic algorithm, has gained increased attention due to its excellent performance in solving many complex problems. This paper incorporates SOS with the feasibility-based rules for solving constrained engineering design problems. The feasibility-based rules were integrated to SOS in order to satisfy the design constraints of each problem. The performance of SOS was compared with the performance of recent optimization algorithms in solving three engineering design problems. The experimental results reveal the potential of the proposed algorithm to deliver solutions at better quality using a smaller number of function evaluations. Results indicate that SOS efficiently solves various complex problems using an approach that is simpler to implement than current widely used methods.