加权
多目标优化
数学优化
帕累托原理
最大值和最小值
理想点,理想点
点(几何)
帕累托最优
集合(抽象数据类型)
数学
价值(数学)
计算机科学
多目标规划
最优化问题
统计
放射科
数学分析
医学
程序设计语言
几何学
出处
期刊:Lecture Notes in Economics and Mathematical Systems
日期:1980-01-01
卷期号:: 468-486
被引量:568
标识
DOI:10.1007/978-3-642-48782-8_32
摘要
SummaryThe paper presents a survey of known results and some new developments in the use of reference objectives—that is, any reasonable or desirable point in the objective space—instead of weighting coefficients or utility (value) functions in multiobjective optimization. The main conclusions are as follows: Any point in the objective space—no matter whether it is attainable or not, ideal or not—can be used instead of weighting coefficients to derive scalarizing functions which have minima at Pareto points only. Moreover, entire basic theory of multiobjective optimization--necessary and sufficient conditions of optimality and existence of Pareto-optimal solutions, etc.—can be developed with the help of reference objectives instead of weighting coefficients or utility (value) functions. Reference objectives are very practical means for solving a number of problems such as Pareto-optimality testing, scanning the set of Pareto-optimal solutions, computer-man interactive solving of multiobjective problems, group assessment of solutions of multiobjective optimization or cooperative game problems, or solving dynamic multiobjective optimization problems.
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