Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107961
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dc.contributor.authorBonyadi, M.en
dc.contributor.authorMichalewicz, Z.en
dc.contributor.authorWagner, M.en
dc.date.issued2014en
dc.identifier.citationProceedings of the 10th International Conference on Simulated Evolution and Learning, 2014 / vol.8886, pp.431-442en
dc.identifier.isbn9783319135625en
dc.identifier.issn0302-9743en
dc.identifier.issn1611-3349en
dc.identifier.urihttp://hdl.handle.net/2440/107961-
dc.description.abstractThe productivity of real-world systems is often limited by so-called bottlenecks. Hence, usually companies are not only interested in finding the best ways to schedule their current resources so that their benefits are maximized (optimization), but, in order to increase the productivity, they also conduct some analysis to find bottlenecks in their system and eliminate them in the most efficient way (e.g., with the lowest investment). We show that the current frequently used analysis (based on average shadow price) for identifying bottlenecks has some limitations: (1) it is limited to linear constraints, (2) it does not consider all potential sources for bottlenecks in a system, and (3) it does not provide adequate tools for decision makers to find the best way of investment to eliminate bottlenecks and maximize the profit they can gain. We propose a more comprehensive definition of bottlenecks that covers these limitations. Based on this new definition, we propose a multi-objective model for the benefit and investment. The solution for this model provides the best way of investment in resources to achieve maximum profit. As the proposed model is multi-objective and non-linear, it opens an important opportunity for the application of evolutionary algorithms, which can subsequently have a significant impact on the decision making process of companies.en
dc.description.statementofresponsibilityMohammad Reza Bonyadi, Zbigniew Michalewicz, and Markus Wagneren
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8886en
dc.rights© Springer International Publishing Switzerland 2014en
dc.subjectConstraints, bottlenecks, what-if analysis, feasibilityen
dc.titleBeyond the edge of feasibility: analysis of bottlenecksen
dc.typeConference paperen
dc.identifier.rmid0030024055en
dc.contributor.conference10th International Conference on Simulated Evolution and Learning (SEAL 2014) (15 Dec 2014 - 18 Dec 2014 : New Zealand)en
dc.identifier.doi10.1007/978-3-319-13563-2_37en
dc.identifier.pubid171881-
pubs.library.collectionComputer Science publicationsen
pubs.library.teamDS06en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]en
Appears in Collections:Computer Science publications

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