Derivative-free Nonlinear Constrained Optimization under Uncertainty Using NOWPAC

来源 :第八届工业与应用数学国际大会 | 被引量 : 0次 | 上传用户:apzhc
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
  We present the derivative-free optimization procedure NOWPAC(Nonlinear Optimization With Path-Augmented Constraints)for nonlinear constrained programming.The algorithm is based on a trust region framework that maintains feasibility at all intermediate designs.
其他文献
  Vaccination coverage in developed countries weakens significantly over concerns regarding the side-effects of the vaccines.As a consequence the non-compulso
会议
  Minimal surfaces are equilibrium surfaces of the area.Triply periodic minimal surfaces in the three-dimensional Euclidean space(TPMS's)sometimes appear in s
会议
  We propose the generalized autoregressive model with exogenous variables on the basis of generalized linear models with location,scale and shape.The propose
会议
  Mathematics for Industry(MI)has been born by amalgamating and reorganizing pure and applied mathematics,to serve as the foundation for future technologies.V
会议
  Mathematics for Industry(MI)has been born by amalgamating and reorganizing pure and applied mathematics,to serve as the foundation for developing future tec
会议
  It is known that a droplet with surface tension gradient can deform and move through the Marangoni effect.We constructed a mathematical model for such dropl
会议
  In this talk,we show how the string method,which was originally developed to compute minimum energy paths between two meta-stable states,can be used to comp
会议
  In this talk,I will use the shortest path problem,finding the shortest path connecting two points while avoiding obstacles in a region,as an example to illu
会议
  Finding minimum energy path(MEP)on a potential energy surface is of great interest in understanding the barrier-crossing events.We develop an adaptive step-
会议
  Linear eigenfunction decomposition is a powerful technique used broadly for processing signals and images.In this talk a generalization based on convex vari
会议