Parallel and Large-Scale Nonlinear Programming

这是一个开发非线性规划算法的项目，特别是多变量问题，重点是适合于并行计算机的算法。重点放在类牛顿方法上。这项研究的动机是早先在开发并行无约束优化算法和软件方面取得的成功。这项研究主要针对适用于粗粒度并行计算机的方法，在粗粒度并行计算机中，每个处理器本身都具有中等的能力。这包括现有的机器，如英特尔iPSC超级立方体和Sequent并行计算机。大规模的非线性规划问题经常出现在工业、经济和军事应用中，而非线性模型往往很难求解。这项研究的目的是产生易于使用的通用算法(和软件)，使并行计算机的能力可用于非线性模型的用户，扩大非线性规划作为日常建模工具的范围。//

This is a project to develop algorithms for nonlinear programming, particularly problems with many variables, with an emphasis on algorithms suitable for parallel computers. The focus is on Newton-like methods. The research is motivated by earlier success in developing algorithms and software for parallel unconstrained optimization. The research is primarily aimed at methods suitable for coarse-grained parallel computers, where each processor is itself moderately powerful. This includes existing machines such as the Intel iPSC hypercube and the Sequent parallel computers. Large-scale nonlinear programming problems arise frequently in industrial, economic, and military applications, however nonlinear models can be difficult to solve. This research aims to produce easy-to-use, general purpose algorithms (and software) that will make available the power of parallel computers to the users of nonlinear models, extending the range of nonlinear programming as a day-to-day modelling tool.//