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During the last three decades, there has been a growing interest in problem-solving systems based on algorithms that rely on analogies to natural processes. Nature-inspired optimization techniques have been proven to be quantitatively appealing, since they have been proved to be robust and efficient even for the most complex problems examined. These methods, also known as metaheuristics, are used for combinatorial optimization problems. The objective of this study is to assess the performance of metaheuristic optimization when implemented for the design of three-dimensional steel structures having single or multiple objectives. Almost every real-world problem involves simultaneous optimization of several incommensurable and often competing objectives, which constitutes a multiobjective optimization problem. In multiobjective optimization problems, the optimal solution is not unique as in single-objective optimization problems. Structural optimization problems are formulated as sizing design optimization, where the cross-sectional dimensions of the structural elements constitute the sizing design variables. In particular, this chapter is concerned with the structural optimization of skeletal truss structures under static loading conditions with single and multiple objectives. Combinatorial optimization methods and in particular algorithms based on evolution strategies are implemented for the solution of both type of problems. |
