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Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster ConvergenceOptimization
Högskolan i Skövde, Forskningscentrum för Virtuella system. Högskolan i Skövde, Institutionen för teknik och samhälle. (Production and Automation Engineering)ORCID-id: 0000-0003-0111-1776
Högskolan i Skövde, Forskningscentrum för Virtuella system. Högskolan i Skövde, Institutionen för teknik och samhälle. (Production and Automation Engineering)
Stockholm University, Sweden.
Michigan State University, USA.
2013 (engelsk)Inngår i: Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / [ed] Giuseppe Nicosia, Panos Pardalos, Berlin, Heidelberg: Springer Berlin/Heidelberg, 2013, s. 1-18Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

This paper introduces a novel methodology for the optimization, analysis and decision support in production systems engineering. The methodology is based on the innovization procedure, originally introduced to unveil new and innovative design principles in engineering design problems. The innovization procedure stretches beyond an optimization task and attempts to discover new design/operational rules/principles relating to decision variables and objectives, so that a deeper understanding of the underlying problem can be obtained. By integrating the concept of innovization with simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis. The uniqueness of the approach introduced in this paper lies in that decision rules extracted from the multi-objective optimization using data mining are used to modify the original optimization. Hence, faster convergence to the desired solution of the decision-maker can be achieved. In other words, faster convergence and deeper knowledge of the relationships between the key decision variables and objectives can be obtained by interleaving the multi-objective optimization and data mining process. In this paper, such an interleaved approach is illustrated through a set of experiments carried out on a simulation model developed for a real-world production system analysis problem.

sted, utgiver, år, opplag, sider
Berlin, Heidelberg: Springer Berlin/Heidelberg, 2013. s. 1-18
Serie
Lecture Notes in Computer Science, ISSN 0302-9743 ; 7997
Emneord [en]
Innovization, Multi-Objective Optimization, Data Mining, Production Systems
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URN: urn:nbn:se:his:diva-10059DOI: 10.1007/978-3-642-44973-4_1Scopus ID: 2-s2.0-84890892997ISBN: 978-3-642-44972-7 (tryckt)ISBN: 978-3-642-44973-4 (tryckt)OAI: oai:DiVA.org:his-10059DiVA, id: diva2:752297
Tilgjengelig fra: 2014-10-03 Laget: 2014-10-03 Sist oppdatert: 2019-05-27bibliografisk kontrollert

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