Size optimization of steel trusses using a genetic algorithm in MATLAB (original) (raw)
2017, Journal of Software Engineering & Intelligent Systems
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.
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