Different Discrete ACCS Algorithms for Optimal Design of Truss Structures: A Comparative Study

Many optimization techniques based on swarm intelligence have been developed for size optimization of skeletal structures. Cuckoo search algorithm, artificial bee colony algorithm, colliding bodies optimization, artificial coronary circulation system (ACCS) are only some examples of these algorithms. In these methods, the sizing variables are often assumed to be continuous. However, in most practical structural engineering design problems, the design variables are discrete. The aim of this study is to present an optimization algorithm based on the ACCS algorithm for the discrete optimum design of truss structures. Here, the discrete search strategy using the ACCS algorithm is presented by three different scenarios in detail and their effectiveness and robustness are compared to those of the recently developed discrete optimization methods. The ACCS optimization algorithm uses the visual center point of populations in each iteration and simulates the process of growing coronary arteries of heart. Finally, it is shown that the discrete ACCS has the fastest convergence rate among the considered algorithms and can be effectively used to solve optimal design of truss structures with discrete variables.