Evolutionary optimization of production materials workflow processes

Luke Thomas Herbert, Zaza Nadja Lee Hansen, Peter Jacobsen, Pedro Cunha

Research output: Contribution to journalConference articleResearchpeer-review

456 Downloads (Pure)

Abstract

We present an evolutionary optimisation technique for stochastic production processes, which is able to find improved production materials workflow processes with respect to arbitrary combinations of numerical quantities associated with the production process. Working from a core fragment of the BPMN language, we employ an evolutionary algorithm where stochastic model checking is used as a fitness function to determine the degree of improvement of candidate processes derived from the original process through mutation and cross-over operations. We illustrate this technique using a case study where a baked goods company seeks to improve production time while simultaneously minimising the cost and use of resources.
Original languageEnglish
JournalProcedia CIRP
Volume25
Pages (from-to)53–60
ISSN2212-8271
DOIs
Publication statusPublished - 2014
Event8th International Conference on Digital Enterprise Technology (DET 2014) - Stuttgart, Germany
Duration: 25 Mar 201428 Mar 2014
Conference number: 8

Conference

Conference8th International Conference on Digital Enterprise Technology (DET 2014)
Number8
CountryGermany
CityStuttgart
Period25/03/201428/03/2014

Keywords

  • Evolutionary algorithm
  • Stocastic BPMN
  • Production optimisation

Fingerprint Dive into the research topics of 'Evolutionary optimization of production materials workflow processes'. Together they form a unique fingerprint.

Cite this