Simulation-based innovization using data mining for production systems analysis
2011 (English)In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb, London: Springer, 2011, 401-429 p.Chapter in book (Refereed)
This chapter introduces a novel methodology for the analysis and optimization of production systems. The methodology is based on the innovization procedure, originally introduced for unveiling new and innovative design principles in engineering design problems. Although the innovization method is based on multi-objective optimization and post-optimality analyses of optimised solutions, it stretches the scope 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 problem can be obtained. By integrating the concept of innovization with discrete-event simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis, particularly suitable for production systems. The uniqueness of the integrated approach proposed in this chapter lies on applying data mining to the data sets generated from simulation-based multi-objective optimization, in order to automatically or semi-automatically discover and interpret the hidden relationships and patterns for optimal production systems design/reconfiguration.
Place, publisher, year, edition, pages
London: Springer, 2011. 401-429 p.
Computer and Information Science
IdentifiersURN: urn:nbn:se:su:diva-99014DOI: 10.1007/978-0-85729-652-8_15ISBN: 978-0-85729-617-7 (Print)ISBN: 978-0-85729-652-8 (Online)OAI: oai:DiVA.org:su-99014DiVA: diva2:686130