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Self-adaptive stepsize search for automatic optimal design

机译：自适应分步搜索，可自动优化设计

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Engineering design involves the determination of a system's design variable values with the aim of obtaining a 'low cost' design that does not violate the system's constraints. For example, in structural design, low weight (hence less material and financial cost) space trusses are required that resist specified external forces without exhibiting excessive displacement or deformation. Unfortunately, the design space is usually vast, so a computer-based approach is a natural way forward for the engineering design process. However, the use of heuristic computational optimization algorithms to automatically obtain an optimal design is usually overlooked by practitioners. This is because of the lack of a standard methodology for matching a suitable optimization algorithm with a particular design problem, and also for the need to first determine the control parameter values of the optimization algorithm prior to actually using the algorithm for design purposes. In this paper a novel population-based computational optimization algorithm, called self-adaptive stepsize search (SASS), is applied to two standard engineering design problems. Computational experiments presented in this paper demonstrate that the algorithm is very effective and also very efficient. Furthermore, it is versatile in the sense that it is not restricted to any particular application area and, importantly, it avoids the usual need to tune the algorithm parameters prior to performing the design optimization. SASS therefore provides design practitioners with a powerful and practical tool which can be used as a black-box optimizer without the need for detailed knowledge of optimization algorithms.
机译：工程设计涉及确定系统的设计变量值，目的是获得不违反系统约束的“低成本”设计。例如，在结构设计中，需要重量轻（因此减少了材料和财务成本）的空间桁架，以抵抗特定的外力而不会出现过度的位移或变形。不幸的是，设计空间通常很大，因此基于计算机的方法是工程设计过程的自然方法。然而，从业人员通常忽略使用启发式计算优化算法来自动获得最佳设计。这是因为缺乏将合适的优化算法与特定设计问题相匹配的标准方法，并且还因为需要在实际将算法用于设计目的之前首先确定优化算法的控制参数值。本文将一种新颖的基于种群的计算优化算法，称为自适应步长搜索（SASS），应用于两个标准工程设计问题。本文提出的计算实验表明该算法非常有效，而且非常有效。此外，从不限于任何特定应用领域的意义上讲，它是通用的，重要的是，它避免了在执行设计优化之前通常需要调整算法参数的情况。因此，SASS为设计人员提供了功能强大且实用的工具，可以用作黑匣子优化器，而无需详细了解优化算法。

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