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

该职业奖支持致力于帮助设计师在概念设计过程中探索和利用设计替代方案的研究工作。将开发一个概念设计系统，该系统可以与设计师合作创建、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备选方案的设计语法，并使用动态编码设计变量的专门遗传算法(GA)来实施。为了帮助探索设计方案，将开发一种基于遗传算法的多目标(MO)方法，对于具有不同结构配置的设计，该方法可以在一次试验中获得S-帕累托边界。为了从S-帕累托集合中选择最佳设计，将使用科霍宁神经网络来捕获用户的设计偏好。这项研究将显著提高设计师设计高效和新颖结构的能力，并将影响设计师对设计过程进行概念化的方式。职业教育活动旨在为学生提供他们未来雇主所希望的技能和经验。一门新的高级顶石设计课程将允许建筑和土木工程专业的学生就专业工程师定义的现实问题进行合作。一门新的启发式方法研究生课程将满足培养跨学科工程师解决复杂优化问题的需求。此外，本科课程还将增加体验式学习模块。教育活动使学生受益于增加他们的设计和优化知识，加强他们对结构行为的理解，并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.