Production fine planning using a solution archive of priority rules

Erik Pitzer, Andreas Beham, Michael Affenzeller, Helga Heiss, Markus Vorderwinkler

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

7 Citations (Scopus)

Abstract

Production Fine Planning is often performed directly using all information and assuming that it is fixed. In practice, however, this information changes regularly and the plan has to be adapted. This often means a complete rescheduling of all operations. We present a new approach to this problem by optimizing priority rules that can sort the available next actions. These priority rules often yield similar results even though they do not resemble each other. By using genetic programming to build these priority rules, a distributed system to compute the simulations and a solution archive with a cache of hundreds of thousands of priority rules, new insights into priority rule-based optimization are gained. This archive does not only speed up calculation by avoiding re-simulation of the same rule but can provide a pseudo Pareto front of shorter sub-optimal solutions that facilitate interpretation of the more complex rules and their evolution during the optimization process.

Original languageEnglish
Title of host publicationLINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings
Pages111-116
Number of pages6
DOIs
Publication statusPublished - 2011
Event3rd IEEE International Symposium on Logistics and Industrial Informatics, LINDI 2011 - Budapest, Hungary
Duration: 25 Aug 201127 Aug 2011

Publication series

NameLINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings

Conference

Conference3rd IEEE International Symposium on Logistics and Industrial Informatics, LINDI 2011
CountryHungary
CityBudapest
Period25.08.201127.08.2011

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