Change search
ReferencesLink to record
Permanent link

Direct link
Interleaving innovization with evolutionary multi-objective optimization in production system simulation for faster convergence
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2013 (English)In: Learning and Intelligent Optimization: 7th International Conference, LION 7, Revised Selected Papers, Springer Berlin/Heidelberg, 2013, 1-18 p.Conference paper (Refereed)
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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. 1-18 p.
, Lecture Notes in Computer Science, ISSN 0302-9743
Keyword [en]
Innovization, Multi-objective optimization, Data mining, Production system simulation
National Category
Information Systems
Research subject
Computer and Systems Sciences
URN: urn:nbn:se:su:diva-97220DOI: 10.1007/978-3-642-44973-4_1ISBN: 978-3-642-44972-7 (Print)ISBN: 978-3-642-44973-4 (Online)OAI: diva2:676264
7th International Conference, LION 7, Catania, Italy, January 7-11, 2013
Available from: 2013-12-05 Created: 2013-12-05 Last updated: 2014-02-03Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Boström, Henrik
By organisation
Department of Computer and Systems Sciences
Information Systems

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 13 hits
ReferencesLink to record
Permanent link

Direct link