Decomposition Topics in Large-Scale Optimization

这项研究的目标是开发大规模优化模型的有效算法。这一发展包括对分解技术的理论和计算研究，这种技术允许将问题划分为更容易处理的子问题。特别令人感兴趣的是大系统的模型，其中拥塞或其他非线性是重要的。所研究的方法适用于运筹学中出现的许多模型，如运输计划、路线和调度、制造和物流。它也适用于在其他工程学科和科学中开发的电气和物理系统的模型。

This research has as its objective the development of effective algorithms for large-scale optimization models. The development includes both theoretical and computational investigation of decomposition techniques which allow division of the problem into more tractable subproblems. Of particular interest are models of large systems in which congestion or other nonlinearities are important. The methodology being investigated is applicable to many models that arise in operations research such as transportation planning, routing and scheduling, manufacturing, and logistics. It is also applicable to models of electrical and physical systems developed in other engineering disciplines and in the sciences.