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Preference Modeling and Model Management for Interactive Multi-objective Evolutionary Optimization

机译：交互式多目标进化优化的偏好建模和模型管理

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摘要

Multiobjective optimization and decision making are strongly inter-related. This paper presents an interactive approach for the integration of expert preferences into multi-objective evolutionary optimization. The experts underlying preference is modeled only based on comparative queries that are designed to distinguish among the non-dominant solutions with minimal burden on the decision maker. The preference based approach constitutes a compromise between global approximation of a Pareto front and aggregation of objectives into a scalar utility function. The model captures relevant aspects of multi-objective decision making, such as preference handling, ambiguity and incommensurability. The efficiency of the approach in terms of number of expert decisions and convergence to the optimal solution are analyzed on the basis of an artificial decision behavior with respect to optimization benchmarks.
机译：多目标优化和决策紧密相关。本文提出了一种将专家偏好整合到多目标进化优化中的交互式方法。仅基于比较查询来建模基础偏好的专家，这些比较查询旨在区分非主导解决方案，而对决策者的负担却最小。基于偏好的方法构成了Pareto前沿的全局逼近与目标汇总成标量效用函数之间的折衷。该模型捕获了多目标决策的相关方面，例如偏好处理，歧义性和不可通约性。根据关于优化基准的人为决策行为，分析了该方法在专家决策数量和收敛到最优解决方案方面的效率。

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