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Temporal Innovization: Evolution of Design Principles Using Multi-objective Optimization
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik)ORCID iD: 0000-0001-5436-2128
Michigan State University, USA.ORCID iD: 0000-0001-7402-9939
2015 (English)In: Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2015), Springer, 2015, Vol. 9018, p. 79-93Conference paper, Published paper (Refereed)
Abstract [en]

Multi-objective optimization yields multiple solutions each of which is no better or worse than the others when the objectives are conflicting. These solutions lie on the Pareto-optimal front which is a lower-dimensional slice of the objective space. Together, the solutions may possess special properties that make them optimal over other feasible solutions. Innovization is the process of extracting such special properties (or design principles) from a trade-off dataset in the form of mathematical relationships between the variables and objective functions. In this paper, we deal with a closely related concept called temporal innovization. While innovization concerns the design principles obtained from the trade-off front, temporal innovization refers to the evolution of these design principles during the optimization process. Our study indicates that not only do different design principles evolve at different rates, but that they start evolving at different times. We illustrate temporal innovization using several examples.

Place, publisher, year, edition, pages
Springer, 2015. Vol. 9018, p. 79-93
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9018
Keywords [en]
Multi-objective Optimization, Design Principles, Innovization, Evolutions
National Category
Computer Sciences Electrical Engineering, Electronic Engineering, Information Engineering Mechanical Engineering
Research subject
Technology; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-11391DOI: 10.1007/978-3-319-15934-8_6ISI: 000361702100006Scopus ID: 2-s2.0-84925326498ISBN: 978-3-319-15934-8 ISBN: 978-3-319-15933-1 OAI: oai:DiVA.org:his-11391DiVA, id: diva2:847278
Conference
8th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2015), 29 March-1 April 2015, Guimarães, Portugal
Projects
KDISCO
Funder
Knowledge Foundation, 20130297Available from: 2015-08-19 Created: 2015-08-19 Last updated: 2018-05-07Bibliographically approved

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Bandaru, SunithDeb, Kalyanmoy

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Citation style
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