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MULTI-OBJECTIVE OPTIMIZATION WITHIN A CONSTRAINT MANAGEMENT SYSTEM

机译:约束管理系统中的多目标优化

摘要

Methods and systems are described for integrating Multi-Objective Optimization (MOO) with a Constraint Management System (CMS) so as to rapidly and flexibly search large design spaces and focus on “interesting” designs as determined by user-specified criteria. An exemplary method embeds the value of a trade space and its trade-off envelope within the same CMS network used to calculate the values of the points in the trade space itself. The exemplary method supports automatic variation of the resulting trade-off analyses in response to variations in upstream parameters, assumptions, and/or requirements not explicitly used in the optimization problem but which nevertheless impact the results. When mathematically feasible, the CMS can back-solve for values of one or more of the upstream parameters so that one or more selected attributes of the trade-off envelope achieve user-specified values. The coupled use of a CMS with multi-objective optimization avoids the extremely laborious procedure of generating a very large set of permutations of inputs and factors and then restricting the analysis to those that have desired outputs or of having the user manually “reformulate” the equation set so that it solves in the desired direction.
机译:描述了将多目标优化(MOO)与约束管理系统(CMS)集成在一起的方法和系统,以便快速灵活地搜索大型设计空间,并专注于由用户指定的标准确定的“有趣”设计。一种示例性方法将交易空间及其权衡包络的值嵌入到用于计算交易空间本身中的点的值的同一CMS网络中。该示例性方法支持响应于上游参数,假设和/或要求中未在优化问题中明确使用但仍会影响结果的上游参数,假设和/或要求的变化而自动对所得的折衷分析进行自动变化。在数学上可行的情况下,CMS可以反求解一个或多个上游参数的值,以便权衡范围的一个或多个选定属性达到用户指定的值。 CMS与多目标优化的结合使用避免了非常费力的过程,该过程会生成大量输入和因子的排列,然后将分析限制为具有所需输出的结果或让用户手动“重新构建”方程式进行设置,以使其按所需方向求解。

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