Testing Soccer League Competition Algorithm in Comparison with Ten PopularMeta-heuristic Algorithms for Sizing Optimization of Truss Structures

Recently, many meta-heuristic algorithms are proposed for optimization of various problems. Some ofthem originally are presented for continuous optimization problems and some others are just applicablefor discrete ones. In the literature, sizing optimization of truss structures is one of the discreteoptimization problems which is solved by many meta-heuristic algorithms. In this paper, in order todiscover an efficient and reliable algorithm for optimization of truss structures, a discrete optimizer,entitled Soccer League Competition (SLC) algorithm and ten popular and powerful solvers areexamined and statistical analysis is carried out for them. The fundamental idea of SLC algorithm isinspired from a professional soccer league and based on the competitions among teams to achievebetter ranking and players to be the best. For optimization purpose and convergence of the initialpopulation to the global optimum, different teams compete to take the possession of the best ratingpositions in the league table and the internal competitions are taken place between players in each teamfor personal improvements. Recently, SLC as a multi-population algorithm with developed operatorshas been applied for optimization of various problems. In this paper, for demonstrating theperformance of the different solvers for optimal design of truss structures, five numerical exampleswill be optimized and the results show that proposed SLC algorithm is able to find better solutionsamong other algorithms. In other words, SLC can discover new local optimal solutions for someexamples where other algorithms fail to find that one.

Keywords:

Optimization of Truss , Genetic Algorithm , Soccer League Competition , Meta-heuristic Algorithms ,