Automatically weighted high-resolution mapping of multi-criteria decision analysis for sustainable manufacturing systems

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dc.contributor.authorPagone, Emanuele
dc.contributor.authorSalonitis, Konstantinos
dc.contributor.authorJolly, Mark R.
dc.date.accessioned2020-02-10T12:00:17Z
dc.date.available2020-02-10T12:00:17Z
dc.date.issued2020-02-01
dc.description.abstractA common feature of Multi-Criteria Decision Analysis (MCDA) to evaluate sustainable manufacturing is the participation (to various extents) of Decision Makers (DMs) or experts (e.g. to define the importance, or “weight”, of each criterion). This is an undesirable requirement that can be time consuming and complex, but it can also lead to disagreement between multiple DMs. Another drawback of typical MCDA methods is the limited scope of weight sensitivity analyses that are usually performed for one criterion at the time or on an arbitrary basis, struggling to show the “big picture” of the decision making space that can be complex in many real-world cases. This work removes all the mentioned shortcomings implementing automatic weighting through an ordinal combinatorial ranking of criteria objectively set by four pre-defined weight distributions. Such solution provides the DM not only with a fast, rational and systematic method, but also with a broader and more accurate insight into the decision making space considered. Additionally, the entropy of information in the criteria can be used to adjust the weights and emphasise the differences between potentially close alternativeen_UK
dc.identifier.citationPagone E, Salonitis K, Jolly M. (2020) Automatically weighted high-resolution mapping of multi-criteria decision analysis for sustainable manufacturing systems. Journal of Cleaner Production, Volume 257, June 2020, Article number 120272en_UK
dc.identifier.cris26127007
dc.identifier.issn0959-6526
dc.identifier.urihttps://doi.org/10.1016/j.jclepro.2020.120272
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15116
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectManufacturing systemen_UK
dc.subjectDecision makingen_UK
dc.subjectSustainable developmenten_UK
dc.subjectCastingen_UK
dc.subjectLifecycleen_UK
dc.titleAutomatically weighted high-resolution mapping of multi-criteria decision analysis for sustainable manufacturing systemsen_UK
dc.typeArticleen_UK

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