Collaborative Research: Implementation of Tabu Search for the Design of Novel Molecules using Parallel Computers

合作研究：使用并行计算机实现新型分子设计的禁忌搜索

• 批准号: 0224764
• 负责人: Kyle Camarda
• 金额: $ 5万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2003-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0224764&HistoricalAwards=false
• 关键词: Collaborative; Research; Implementation; Tabu; Search

Research:Product design methodology is a mechanism that permits the synthesis of new materials with specifically tailored properties. Two challenges in computational molecular design are (1) the ability to predict the physical and chemical properties of a given molecule and (2) the ability to solve the large optimization problem which arises from the search for the best molecule for a given application. Research in molecular characterization can predict many physical and chemical properties to a reasonable accuracy for common molecules. A missing technology is a set of parallel algorithms which can efficiently solve the large mixed-integer optimization problems using parallel computing hardware. This project focuses the application of tabu search, a stochastic technique for the solution of such optimization problems, to the molecular design of novel polymers.Tabu search uses a neighborhood search algorithm which is efficient at searching the entire solution space, thus enabling globally optimal solutions to be found within a reasonable time. These algorithms are amenable to parallelization since each member of a solution set can be updated independently. As part of this project, the PIs plan to develop a parallel implementation suitable for use on clusters of workstations. The work will focus on the development of improvements to handle the types of constraint that occur when predicting the physical properties of polymers, and the application of these improvements within a parallel implementation for use on clusters of multiprocessor workstations.Impact:-Tailor-made molecules have huge potential in the chemical process industries. -This Small Grant for exploratory research will permit two young PIs to venture into a totally new research area for them. -This collaborative project between an undergraduate institution, Rose-Hulman, and the University of Kansas, will provide opportunities to undergraduates to be involved in research otherwise not open to them.

研究：产品设计方法论是一种允许合成具有特定定制特性的新材料的机制。计算分子设计中的两个挑战是(1)预测给定分子的物理和化学性质的能力和(2)解决由为给定应用寻找最佳分子而产生的大型优化问题的能力。分子表征的研究可以对常见分子的许多物理和化学性质进行合理准确的预测。缺少的一项技术是一套能够利用并行计算硬件高效地解决大型混合整数优化问题的并行算法。禁忌搜索是一种求解此类优化问题的随机技术，它应用于新型聚合物的分子设计。禁忌搜索采用邻域搜索算法，能够高效地搜索整个解空间，从而在合理的时间内找到全局最优解。这些算法易于并行化，因为解集的每个成员都可以独立更新。作为该项目的一部分，投资促进机构计划开发一种适用于多个工作站集群的并行实施方案。这项工作将集中于开发改进，以处理预测聚合物物理性质时出现的约束类型，并将这些改进应用于多处理器工作站集群的并行实施中。影响：-量身定做的分子在化学加工行业具有巨大的潜力。-这笔用于探索性研究的小额赠款将允许两名年轻的私人投资者冒险进入一个全新的研究领域。-这是一个本科生机构Rose-Hulman与堪萨斯大学的合作项目，将为本科生提供参与其他方面不对他们开放的研究的机会。