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Interactive NBI and (E)NNC methods for the progressive exploration of the criteria space in multi-objective optimization and optimal control

机译:交互式NBI和(E)NNC方法,用于在多目标优化和最优控制中逐步探索标准空间

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摘要

A wide range of problems arising from real world applications present multiple and conflicting objectives to be simultaneously optimized. However, this multi-objective nature is too often neglected. Multi-objective optimization proved to be a powerful tool to correctly describe the trade-offs among conflicting objectives in a set of optimal solutions known as the Pareto set. This paper introduces an interactive method to solve multi-objective problems based on geometric considerations. The method returns a wider Pareto set, at a negligible computational cost, when compared to existing methods. The interactivity also allows the decision-maker to explore only relevant parts of the Pareto set. The extreme solutions yield insightful considerations on the generation of the scalarization parameters for the Normal Boundary Intersection and the Enhanced Normalized Normal Constraints methods. The proposed method is applied to: (ⅰ) three scalar multi-objective problems and (ii) the multi-objective optimal control of a tubular and a fed-batch reactor.
机译:实际应用中产生的许多问题提出了多个目标,这些目标需要同时进行优化。但是,这种多目标性质经常被忽略。事实证明,多目标优化是一种功能强大的工具,可以在一组称为Pareto集的最佳解决方案中正确描述相互矛盾的目标之间的取舍。本文介绍了一种基于几何考虑的交互式方法来解决多目标问题。与现有方法相比,该方法以可忽略的计算成本返回了更广泛的Pareto集。交互性还允许决策者仅探索帕累托集的相关部分。极端解法对法向边界相交的标量化参数的生成和增强型归一化法向约束方法产生了深刻的考虑。所提出的方法适用于:(ⅰ)三个标量多目标问题和(ii)管式和分批进料反应器的多目标最优控制。

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