Automatic problem identifier and parameter tuning in local optimization

局部优化中的自动问题识别和参数调整

• 批准号: 483291-2015
• 负责人: Lu, Zhaosong
• 金额: $ 1.82万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=583446
• 关键词: Automatic; problem; identifier; parameter; tuning

Many engineering problems require optimization of highly complex simulations in order to achieve the best product or process design. In practice, high dimensionality, computational cost and lack of mathematical expressions are three key issues in modern optimization, and their combination makes the design optimization very challenging. Empower Operations, based in BC, is a company which offers design exploration and optimization software suitable for High dimensional, Expensive and Black-box (HEB) problems, to be used by manufacturers. Manufacturers need to use optimization in the design of their product, but not all companies have optimization specialists who can work with optimization codes. The current available optimization methods all require the user to choose the suitable approach for a given problem. Moreover, each method has special parameters which should be tuned. These became the hurdle for practical application of the otherwise powerful optimization. The product of Empower Operations, OASIS (Optimization Assisted Simulation Integration Software), aims to provide a framework in which the user can use global optimization algorithms, with minimum knowledge about the algorithm details. The OASIS software contains a module for local optimization but little work is done to find the best method for different problems. In this project, the objective is to find a strategy to identify the type of problem and tune algorithm parameters automatically, with the purpose of solving a wider range of problems. The proposed research will significantly enhance the performance of the OASIS optimization algorithm, and make OASIS accessible to a wider scope of design engineers. The developed techniques can bridge the gap between optimization theory and practical demand from engineers, and ultimately increase the global competitiveness of Canadian manufacturers.

许多工程问题需要优化高度复杂的模拟，以实现最佳 产品或过程设计。实际上，高维，计算成本和缺乏数学 表达是现代优化的三个关键问题，它们的组合使设计优化 非常具有挑战性。位于不列颠哥伦比亚省的Empower Operations是一家提供设计探索和的公司 优化软件适用于高维，昂贵且黑色框（HEB）问题，将由 制造商。制造商需要在其产品设计中使用优化，但并非所有公司 拥有可以使用优化代码的优化专家。当前可用的优化 方法都要求用户为给定问题选择合适的方法。而且，每种方法都有 应该调整的特殊参数。这些成为实际应用否则的障碍 强大的优化。 授权操作的产物绿洲（优化辅助模拟集成软件）旨在 提供一个框架，用户可以使用全局优化算法（具有最低知识） 关于算法详细信息。 OASIS软件包含一个用于本地优化的模块，但很少的工作是 为了找到解决不同问题的最佳方法。在这个项目中，目的是找到一种策略来识别 问题和调谐算法参数的类型自动，目的是解决更广泛的范围 问题。拟议的研究将显着提高绿洲优化的性能 算法，使绿洲可用于更广泛的设计工程师。开发的技术可以 弥合优化理论与工程师实际需求之间的差距，并最终增加 加拿大制造商的全球竞争力。