Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts

被引:81
作者
Jakob, Wilfried [1 ]
Blume, Christian [2 ]
机构
[1] KIT, Inst Appl Comp Sci IAI, POB 3640, D-76021 Karlsruhe, Germany
[2] Cologne Univ Appl Sci, Inst Automat & Ind IT, D-51643 Gummersbach, Germany
关键词
multi-criteria optimization; Pareto optimization; weighted sum; cascaded weighted sum; global optimization; population based optimization; evolutionary algorithm;
D O I
10.3390/a7010166
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:166 / 185
页数:20
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