Paper Title
Truss Optimization using Genetic Algorithm

In this paper, a genetic algorithm is proposed to solve the weight minimization problem of truss structures considering shape, and sizing design variables. Design variables are discrete or/and continuous. The design of truss structures is optimized by an efficient optimization algorithm called Teaching-Learning-Based Optimization (TLBO). The process of TLBO is divided into two parts: the first part consists of the „Teacher phase‟ and the second part consists of the „Learner phase‟. Analyses of structures are performed by a finite element code in MATLAB which is used in conjunction with an optimization code based on TLBO. The effectiveness of TLBO algorithm is demonstrated through benchmark truss 18-bar, and compare with results in references. Keywords–Planar Truss, Size And Shape Optimization, Discrete And Continuous Variables, TLBO Algorithm.