Information extraction from solution set of simulation-based multi-objective optimization using data mining
2009 (English)In: Proceedings of Industrial Simulation Conference (ISC) 2009, 2009, 65-69 p.Conference paper (Refereed)
In this work, we investigate ways of extracting information from simulations, in particular from simulation-based multi-objective optimisation, in order to acquire information that can support human decision makers that aim for optimising manufacturing processes. Applying data mining for analyzing data generated using simulation is a fairly unexplored area. With the observation that the obtained solutions from a simulation-based multi-objective optimisation are all optimal (or close to the optimal Pareto front) so that they are bound to follow and exhibit certain relationships among variables vis-à-vis objectives, it is argued that using data mining to discover these relationships could be a promising procedure. The aim of this paper is to provide the empirical results from two simulation case studies to support such a hypothesis.
Place, publisher, year, edition, pages
2009. 65-69 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:su:diva-98567OAI: oai:DiVA.org:su-98567DiVA: diva2:684429
Industrial Simulation Conference 2009