TEACHING-LEARNING-BASED OPTIMIZATION ALGORITHM FOR SHAPE AND SIZE OPTIMIZATION OF TRUSS STRUCTURES WITH DYNAMIC FREQUENCY CONSTRAINTS

Due to the aforementioned obstacles in optimization of shape and sizing of structures with multiple frequency constraints, the choice of the solution method is of great importance and local search algorithms are not appropriate. As indicated by Gomes [11], traditional optimization methods based on gradients also have difficulties in problems with repeated eigenvalues and may trap into local optima. As powerful alternative methods, modern metaheuristic algorithms, which are not based on gradients, can be successfully employed to solve the problem. They are also capable of solving highly non-linear problems with complex objective functions. Due to their effectiveness in dealing with real-life complicated problems, new metaheuristics are frequently proposed. For example, among the most recently developed metaheuristics, Water Cycle Algorithm (WCA) [12], Mine Blast Algorithm (MBA) [13], Cuckoo Optimization Algorithm (COA) [14] can be mentioned. Some hybrid optimization algorithms have also been presented which make use of two or several metaheuristics and local search methods in order to improve their performance in dealing with trusses and other structures [15, 16]. However, use of metaheuristic optimization methods in optimization of shape and size of trusses with multiple frequency constraints have received little attention in the literature. Recently, Gomes [11] implemented Particle Swarm Optimization (PSO) algorithm to optimize the shape and size of truss structures with multiple frequency constraints. Later, Miguel and Miguel [17] utilized two other metaheuristics, i.e. Harmony Search (HS) method and Firefly Algorithm (FA) to solve this kind of problem. A combination of the Charged System Search (CSS) and the Big Bang-Big Crunch (BBC) algorithms has been recently employed by Kaveh and Zolghadr [18] for truss optimization with natural frequency constraints. In this paper, a recently developed metaheuristic, called teaching-learning-based optimization (TLBO) algorithm is used for the first time to solve the problem of truss shape and size optimization with multiple frequency constraints. TLBO has some inherent capabilities and advantages compared to other metaheuristic approaches. It is reported that it outperforms most metaheuristics regarding constrained benchmark functions, constrained mechanical design, and continuous non-linear numerical optimization problems [19]. However, the effectiveness of TLBO in shape and size optimization of truss structures w