{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T13:50:07Z","timestamp":1779198607515,"version":"3.51.4"},"reference-count":25,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,3,21]],"date-time":"2014-03-21T00:00:00Z","timestamp":1395360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Algorithms"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/a7010166","type":"journal-article","created":{"date-parts":[[2014,3,21]],"date-time":"2014-03-21T12:06:20Z","timestamp":1395403580000},"page":"166-185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":105,"title":["Pareto Optimization or Cascaded Weighted Sum:  A Comparison of Concepts"],"prefix":"10.3390","volume":"7","author":[{"given":"Wilfried","family":"Jakob","sequence":"first","affiliation":[{"name":"Karlsruhe Institute of Technology (KIT), Institute of Applied Computer Science (IAI),  P.O. Box 3640, Karlsruhe 76021, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Blume","sequence":"additional","affiliation":[{"name":"Cologne University of Applied Sciences, Institute of Automation and Industrial IT,  Steinm\u00fcllerallee 1, Gummersbach 51643, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,3,21]]},"reference":[{"key":"ref_1","unstructured":"Pareto, V. (1896). Cours d\u2019\u00c9conomie Politique, F. Rouge. (in French)."},{"key":"ref_2","unstructured":"Hoffmeister, F., and B\u00e4ck, T. (1992). Genetic Algorithms and Evolution Strategies: Similarities and Differences, FB Informatik, University of Dortmund. Technical Report SYS-1\/92."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Branke, J., Deb, K., Miettinen, K., and S\u0142owi\u0144ski, R. (2008). Multiobjective Optimization: Interactive and Evolutionary Approaches, Springer. 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