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Correction published on 2 April 2014, see Algorithms 2014, 7(2), 188.

Open AccessArticle
Algorithms 2014, 7(1), 166-185; doi:10.3390/a7010166

Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts

1
Karlsruhe Institute of Technology (KIT), Institute of Applied Computer Science (IAI), P.O. Box 3640, Karlsruhe 76021, Germany
2
Cologne University of Applied Sciences, Institute of Automation and Industrial IT, Steinmüllerallee 1, Gummersbach 51643, Germany
*
Author to whom correspondence should be addressed.
Received: 22 January 2014 / Revised: 3 March 2014 / Accepted: 14 March 2014 / Published: 21 March 2014
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Abstract

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. View Full-Text
Keywords: multi-criteria optimization; Pareto optimization; weighted sum; cascaded weighted sum; global optimization; population based optimization; evolutionary algorithm multi-criteria optimization; Pareto optimization; weighted sum; cascaded weighted sum; global optimization; population based optimization; evolutionary algorithm
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Jakob, W.; Blume, C. Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts. Algorithms 2014, 7, 166-185.

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