CAREER: Development of Physical Programming for Robust Computational Design

这项赠款为开发一种新的工程设计计算优化方法提供资金，称为“物理编程”。 这种方法的目的是使它有可能优化物理系统的计算环境中，不需要使用系统属性的数值权重。 这些权重的正确数值通常很难确定，反映了不同设计目标之间的冲突程度。 而不是使用权重，物理编程允许设计师通过为每个设计目标指定几个不同程度的期望范围来表达他/她的偏好。 这种新的方法是为了带来简单，并减少计算负担的优化过程。 物理编程和相关计算算法的理论基础将被开发，以及利用物理编程形式主义的优化可视化方法。 该补助金还要求为大四学生和一年级研究生开发一门以实践为导向的设计优化课程。 本课程的目的是让学生有效地使用优化在工业环境中，使用物理编程。 如果成功，这项研究的结果将导致物理编程的发展，以达到商业和工业适用性。 近年来，工业界显著增加了优化的使用，以改善产品设计。 目前，大多数工业工程师在日常工作中无法有效和可靠地使用优化。 两个主要原因是：（1）优化所需的专业水平，以及（2）使用基于权重的方法表达设计者偏好的困难。 拟议的研究将解决上述困难，也将提供一个新的和更灵活的框架，以解决线性和非线性规划问题。

This grant provides funding for the development of a new computational optimization method for engineering design called `physical programming`. This method is intended to make it possible to optimize physical systems in a computational environment that does not require the use of numerical weights on system attributes. The correct numerical values of these weights, which are typically difficult to identify, reflect the degree of conflict between the different design objectives. Rather than using weights, physical programming allows the designer to express his/her preferences by specifying several ranges of differing degrees of desirability for each design objective. This new approach is intended to bring simplicity, and reduced computational burden to the optimization process. The theoretical foundation of physical programming and related computational algorithms will be developed, together with optimization visualization methods that exploit the physical programming formalism. This grant also calls for the development of a practice-oriented course in design optimization for seniors and first-year graduate students. The objective of this course is to equip students to effectively use optimization in industrial settings, using physical programming. If successful, the outcome of this research will result in the development of physical programming to the point of commercial and industrial applicability. In recent years, industry has significantly increased its use of optimization to improve product designs. Presently, the effective and reliable use of optimization is not within the reach of most industry engineers on a day-to-day basis. Two main reasons are: (1) the required level of expertize in optimization, and (2) the difficulty of expressing the designer's preferences using weight-based methods. The proposed research will address the above-stated difficulties; and will also provide a new and more flexible framework to address linear and nonlinear programming problems.