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:斜拉桥的设计需要确定多个设计变量的值。通常情况下土木工程师会手动迭代多次,直到满足工程成本和结构约束的要求。这一任务极具挑战性,因为改变其中一个变量可能会影响到其他变量,意味着它们不是独立的,从而导致需要探索搜索空间。本文比较了以下两种方法与基准解的一种方法:遗传算法和CMA-ES算法。设计斜拉桥时有两个目标:降低工程成本,同时保证结构约束可以在安全范围内。这些目标是冲突的,这意味着降低成本通常会产生结构不安全的桥梁。结果表明,相比于基准解,CMA-ES算法更好地实现了搜索空间中的良好解,且仅使用相同的计算次数,而遗传算法则无法做到。具体而言,CMA-ES算法能够设计出更为经济且结构安全的桥梁。