Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts

Algorithms

Wilfried Jakob¹ 

[1] Karlsruhe Institute of Technology (KIT), Institute of Applied Computer Science (IAI), P.O. Box 3640, Karlsruhe 76021, Germany

关键词: multi-criteria optimization;    Pareto optimization;    weighted sum;    cascaded weighted sum;    global optimization;    population based optimization;    evolutionary algorithm;   

DOI  :  10.3390/a7010166

来源: mdpi

【 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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.