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Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts

机译:帕累托优化或级联加权和:概念比较

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Looking at articles or conference papers published since the turn of the century, Pareto optimization is the dominating assessment method for multi-objective nonlinear optimization problems. However, is it always the method of choice for real-world applications, where either more than four objectives have to be considered, or the same type of task is repeated again and again with only minor modifications, in an automated optimization or planning process? This paper presents a classification of application scenarios and compares the Pareto approach with an extended version of the weighted sum, called cascaded weighted sum, for the different scenarios. Its range of application within the field of multi-objective optimization is discussed as well as its strengths and weaknesses.
机译:回顾世纪之交以来发表的文章或会议论文,帕累托优化是多目标非线性优化问题的主要评估方法。但是,对于在自动化优化或计划过程中必须考虑四个以上目标,还是一次又一次的微小修改就一次又一次地重复相同类型任务的现实世界中,应用程序始终是首选方法吗?本文介绍了应用场景的分类,并将帕累托方法与针对不同场景的加权和的扩展版本(称为级联加权和)进行了比较。讨论了它在多目标优化领域中的应用范围以及其优缺点。

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