The design of cable-stayed bridges requires the determination of several design variables' values. Civil engineers usually perform this task by hand as an iteration of steps that stops when the engineer is happy with both the cost and maintaining the structural constraints of the solution. The problem's difficulty arises from the fact that changing a variable may affect other variables, meaning that they are not independent, suggesting that we are facing a deceptive landscape. In this work, we compare two approaches to a baseline solution: a Genetic Algorithm and a CMA-ES algorithm. There are two objectives when designing the bridges: minimizing the cost and maintaining the structural constraints in acceptable values to be considered safe. These are conflicting objectives, meaning that decreasing the cost often results in a bridge that is not structurally safe. The results suggest that CMA-ES is a better option for finding good solutions in the search space, beating the baseline with the same amount of evaluations, while the Genetic Algorithm could not. In concrete, the CMA-ES approach is able to design bridges that are cheaper and structurally safe.

翻译：斜拉桥设计需要确定多个设计变量的取值。土木工程师通常通过手动迭代方式完成这一任务，当工程师对方案的成本及结构约束均满意时即停止迭代。该问题的难点在于：改变某个变量可能会影响其他变量，表明这些变量并非相互独立，这暗示我们正面临一个具有欺骗性的优化空间。本研究将两种方法与基准方案进行了比较：遗传算法和CMA-ES算法。桥梁设计面临两个目标：最小化成本以及将结构约束控制在可接受的安全范围内。这两个目标相互冲突，降低成本往往会导致桥梁结构不安全。结果表明，CMA-ES是在搜索空间中寻找优质解的更优选择，在相同评估次数下超越了基准方案，而遗传算法未能实现这一点。具体而言，CMA-ES方法能够设计出造价更低且结构安全的桥梁。