期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 239, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.chemolab.2023.104850
关键词
Desirability; Gradient norm; Optimization; Pareto; RSM; Implementation errors
Researchers and practitioners often face problems with multiple objectives that have conflicting solutions and no unique solution. This paper proposes a novel metric to assess the resilience of Pareto solutions to avoid wasting resources and time on solutions that do not produce the expected outcomes.
Processes and products are multidimensional so researchers and practitioners have to solve problems with multiple objectives frequently. These problems have, in general, responses in conflict so they do not have a unique solution. Different approaches have been proposed in the literature to solve these problems, but many of them, including the popular desirability function approach, are not employed with the focus on the generation of Pareto frontiers. In addition, it is important to stress that some Pareto solutions may not yield the expected outcome(s) when implemented in practice. Thus, to avoid wasting resources and time in implementing a theo-retical solution which does not produce the expected outcome(s), in this paper is proposed a novel metric to assess the resilience of Pareto solutions. This way, the decision-maker may identify a solution less sensitive to changes in the variables setting when their values are implemented in production process (equipments) or during its operation. Metric usefulness is illustrated using a case study, and results analysis is complemented with plots that facilitate the decision-making process.
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