Optimization of Large-Scale Dynamic Systems with Special Reference to Energy Resources

特别涉及能源资源的大型动态系统优化

• 批准号: 8617905
• 负责人: George Dantzig
• 金额: $ 5.08万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-08-01 至 1989-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8617905&HistoricalAwards=false
• 关键词: Optimization; Large; Scale; Dynamic; Systems

The overall objective of this research is to develop techniques for formulating and solving (optimizing) large-scale models of complex systems and to encourage their application. The research on optimization includes techniques for solving large-scale, multi-stage (staircase, dynamic) linear-programming models, their extension to take into account uncertainty, and the solving of certain classes of nonlinearly constrained (large-scale but sparse) systems such as those that arise in equilibrium analysis. The research includes methodology for complex models used to assess the effects of resource scarcity or changes technology through modernization, innovation, and computerization, and also models used for long-term planning, scheduling and control of complex engineering systems such as those that distribute energy. The research on modeling includes ways to formulate models of large complex systems; better ways to express end condition in dynamic models; ways to reformulate models more compactly; ways to use high-speed sampling methods (such as parallel processors) to simulate random events in order to formulate constraints that represent a hedge against uncertainty; and better ways to understand, maintain and update the extensive data bases and large number of constraints used to specify models. The overall objective of this research is to develop techniques for formulating and optimizing large-scale models of complex systems. The optimization techniques which will be developed will be implemented on the computer and the resulting programs will be available for use on a wide variety of large optimization problems.

这项研究的总体目标是开发技术， 用于制定和解决（优化）复杂的大规模模型 并鼓励其应用。 研究 优化包括解决大规模、多阶段问题的技术 （阶梯，动态）线性规划模型，其扩展到 考虑到不确定性，并解决某些类别的 非线性约束（大规模但稀疏）系统，例如 在均衡分析中出现的问题。 研究包括方法论 用于评估资源稀缺影响的复杂模型， 通过现代化、创新来改变技术， 计算机化，以及用于长期规划的模型， 调度和控制复杂的工程系统，如 来分配能量。 建模的研究包括如何 制定大型复杂系统的模型;更好的方式来表达结束 动态模型中的条件;重新制定模型的方法更多 compatible;使用高速采样方法（如并行 处理器）来模拟随机事件，以制定 限制，代表对冲不确定性;以及更好的 了解、维护和更新广泛数据库的方法， 用于指定模型的大量约束。 这项研究的总体目标是开发技术， 用于制定和优化复杂系统的大规模模型。 将开发的优化技术将是 在计算机上实现，产生的程序将 可用于各种大型优化问题。