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In designing complex systems, the quest for optimality often leads to frustration and inefficiency. The use of the optimization construct using the gradient-based solution algorithms result in single-point optimal solution that meet rigorous Karush–Kuhn–Tucker (KKT) conditions. However, these algorithms need to be revised when faced with the complexities of engineering design problems: nonlinear, nonconvex objectives, constraints and objectives with different units, and mathematical models that are abstractions of reality.

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Research Questions: How Can We Realize Model Evolution

  • 章节

  • 发表日期：

    2026年

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  • Lin Guo,
  • Janet K. Allen,
  • Farrokh Mistree

摘要

In designing complex systems, the quest for optimality often leads to frustration and inefficiency. The use of the optimization construct using the gradient-based solution algorithms result in single-point optimal solution that meet rigorous Karush–Kuhn–Tucker (KKT) conditions. However, these algorithms need to be revised when faced with the complexities of engineering design problems: nonlinear, nonconvex objectives, constraints and objectives with different units, and mathematical models that are abstractions of reality.