Sizing Optimization of Truss Structures with Continuous Variables by Artificial Coronary Circulation System Algorithm

Abstract

In the last two decades, many researchers have developed various kinds of metaheuristic algorithms in order to overcome the complex nature of the optimum design of structures. In this paper, a new and simple optimization algorithm is presented to solve weight optimization of truss structures with continuous variables. A very recently developed metaheuristic method called artificial coronary circulation system algorithm (ACCS) is applied to sizing optimization of truss structures. Artificial coronary circulation system optimization algorithm uses the visual center point of populations on each iteration. Therefore, with use of this center point, the ACCS becomes faster and can easily find the best solution of problems with higher efficiency. Here, the ACCS is utilized for truss optimization problems. The heart memory and boundary handling strategy are used in the ACCS algorithm. The suitability of the ACCS for truss optimization is investigated by solving four classical weight minimization problems of truss structures including sizing optimization problems. The viability and efficiency of the proposed method are demonstrated for truss structures subjected to multiple loading conditions and constraints on member stresses and nodal displacement. At the end, some numerical results are compared to those reported in the literature.