CAREER: Enhancing Conceptual Design Using Multi-Objective, Dynamically Encoded Genetic Algorithms to Optimize Structural Toplogy, Geometry, and Size

这个职业奖支持的研究工作，重点是协助设计师在概念设计过程中探索和利用设计方案。 将开发一个概念设计系统，该系统可以与设计师合作，以创建，评估和优化各种设计方案。 将与专业工程师合作开发用于表示复杂的大规模屋顶系统设计方案的设计语法，并使用专门的遗传算法（GA）对设计变量进行动态编码。 为了帮助探索设计方案，将开发基于GA的多目标（MO）方法，该方法可在具有不同结构配置的设计的单次试验中获得s-Pareto前沿。 为了从s-Pareto集合中选择最佳设计，Kohonen神经网络将用于捕获用户的设计偏好。 这项研究将显着提高设计师的能力，设计高效和新颖的结构，并将影响设计师的设计过程中概念化的方式。 职业教育活动旨在为学生提供未来雇主所需的技能和经验。 一个新的高级顶点设计课程将允许建筑和土木工程专业的学生合作解决专业工程师定义的现实问题。 一个新的启发式方法研究生课程将满足培训跨学科工程师解决复杂优化问题的需求。 此外，体验式学习模块将被添加到本科课程。 这些教育活动使学生受益，增加了他们对设计和优化的知识，加强了他们对结构行为的理解，更好地为他们成为未来的设计创新者做好准备。

This CAREER award supports research efforts focused on assisting designers in exploring and exploiting design alternatives during conceptual design. A conceptual design system will be developed that can be teamed with designers to create, evaluate, and optimize diverse design alternatives. A design grammar for representing complex, large-scale roof system design alternatives will be developed in collaboration with professional engineers and implemented using a specialized genetic algorithm (GA) that dynamically encodes the design variables. To assist in exploring design alternatives, a GA-based multi-objective (MO) method will be developed that obtains the s-Pareto frontier within a single trial for designs having different structural configurations. To select the best design from the s-Pareto set, a Kohonen neural network will be used to capture the user's design preferences. This research will significantly enhance a designer's ability to design efficient and novel structures and will influence the way designers conceptualize the design process. The CAREER educational activities seek to provide students with the skills and experience desired by their future employers. A new senior capstone design course will allow architectural and civil engineering students to collaborate on realistic problems defined by professional engineers. A new graduate course in heuristic methods will meet the demand for training interdisciplinary engineers to solve complex optimization problems. In addition, experiential learning modules will be added to undergraduate courses. The educational activities benefit students by increasing their knowledge of design and optimization, strengthening their understanding of structural behavior, and better preparing them to become future design innovators.