JOURNAL OF SOFTWARE ENGINEERING & INTELLIGENT SYSTEMS ISSN 2518-8739 31 st December 2017, Volume 2, Issue 3, JSEIS, CAOMEI Copyright © 2016-2017 www.jseis.org 216 Size optimization of steel trusses using a genetic algorithm in MATLAB Ersilio Tushaj Polytechnic University of Tirana, Albania Email: ersilio.tushaj@gmail.com ABSTRACT An important aspect of any engineering design problem is to achieve efficiency and efficacy. This can be in terms of energy consumption, performance, time, total weight and costs. In many cases, there are multiple solutions to a problem and you should select the one which satisfies better the criteria. This engineering design process is known as optimization. Optimization plays an important role in various engineering applications. Engineers are in continuity, challenged to design structures that use the least amount of resources and satisfy the structural requirements. The optimal design of structures can be decomposed into three major categories: topology, shape and size optimization. These methods have evolved with time and they may be divided in two maxi-groups: deterministic and non-deterministic algorithms. Size optimization of non-deterministic methods with genetic algorithms (GA) are investigated in this article and applied to some steel trusses in MATLAB soft R2017a. This is done by building an algorithm consisting in scripts and sub-functions, which are applied to the trusses for different constraints on stresses, displacements and buckling, depending on the case analyzed. Different values for the GA parameters are analyzed in such way to achieve the best design. The results are put in comparison with previous studies. Keywords: genetic algorithm; steel trusses; structural optimization; engineering; optimization; performance; 1. INTRODUCTION Reducing costs while meeting performance standards is a common challenge in structural design. Engineers typically rely on experience and standardized design procedures to make their structures more efficient [1]. A lot of systematic methods based on mathematical algorithms and grouped under the generic name of Structural Optimization are available to help designing efficient structures. Optimization is a vast field of mathematics whose theory is still actively being developed. But when applied to structural engineering, it is essentially regarded as a helpful to the engineer willing to design more efficient structures. Optimization of steel trusses has been largely investigated by authors from the beginning of structural optimization in civil engineering. The first who gave a mathematical formulation of nonlinear optimization of steel trusses was Schmit in 1960 [2]. Others will follow introducing better performant algorithms which can offer more reliable solutions at a minor time [3]. Optimization of steel trusses, with the developments of programming and computers, can be considered as an integration of knowledges in structural matrix analysis, optimization algorithms, and computer programming. Kirsch [4] in his book Structural optimization: Fundamentals and applications, reported the necessary step to follow a total layout optimization using matrix analysis of monodimensional structures and deterministic optimization techniques. 2. PREVIOUS STUDIES AND GENETIC ALGORITHMS IN STRUCTURAL OPTIMIZATION Different algorithms have been applied successfully in the steel structural design. A survey was prepared by the same author of this paper in [5]. Previous state of the art and reviews in structural size optimization have been prepared by different authors [6-9]. Optimization of steel structures have been largely studied in the international literature. Stasa [10] is an albanian case, from the Polytechnic University of Tirana. In her PhD Dissertation in 1994, she analyzed the optimal design of steel trusses using two deterministic methods: the Fully Stressed Design (FSD) and the Sequential Linear Programming with move limits (SLP). For each algorithm applied and constraints imposed, were given the results of the optimal weight and the final design of the steel elements. The Objective Function imposed was the minimal weight of the trusses. Stresses, displacement and slenderness criteria were applied to the problem. Comparisons were reported between the two methods. Hasancebi, 2009 [11], has studied the performance of some non-deterministic algorithms applied to the optimum design of steel trusses. Chain, 2015 [12] has done a survey on deterministic approaches applied to steel structures design. A state of the art in the use of genetic algorithms in structural optimization was prepared by Pezeshk as a chapter in the Report in Recent Advances in Optimal Structural Design, in 2002 [13].