The ever-increasing demand on engineers to lower production costs to withstand global competition has prompted engineers to look for rigorous methods of decision making, such as optimization methods, to design and produce products and systems both economically and efficiently . Optimization techniques, having reached a degree of maturity in recent years, are being used in a wide spectrum of industries, including aerospace, automotive, chemical, electrical, construction, and manufacturing industries. In some aspects it can be associated with cost optimization, since it obviously leads to an optimal material usage. In civil engineering, weight optimized structures are convenient since there is a combination of transportation and construction with the buildup is simplified. Another advantage of having a weight optimized structure is that a minimum share of the load-capacity is engaged by the structure itself. An efficient optimization technique is the use of genetic algorithms. GA, as it is most commonly referred to, is a type of evolutionary programming and probably the best-known today. It simulates the evolutionary principle of survival of the fittest by combining the best solutions to a problem in many generations to gradually improve the result. The initial population of solutions is created randomly, and as the evolution goes, the best individuals are combined in each generation until an optimal solution converges
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