Hybrid ACO-CI Algorithm for Beam Design Problems

The complexity of real-world problems motivates the development of several optimization algorithms. In this paper, a novel hybrid metaheuristic algorithm is presented by combining the complementary properties of a swarm-based Ant Colony Optimization (ACO) and a socio-inspired Cohort Intelligence (CI) algorithm. It is referred to as hybrid ACO-CI. The ACO-CI algorithm is tested by solving unconstrained standard benchmark test functions. The proposed algorithm is further modified to solve constrained problems in the design engineering domain. The effectiveness of the proposed algorithm is evaluated relative to widely used metaheuristic algorithms. It is observed that the hybrid ACO-CI algorithm obtains comparable results with less computation cost.