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Abstract
The problem of selecting which suppliers, and how much of different items to order from each, involves multiple, often conflicting, criteria such as costs and delivery times. Within real world multi-criteria supplier selection problems there is inherent uncertainty involved, and consideration of its impacts and mitigation is a current and important research direction going forward within the field of supplier selection.
Uncertainty within multi-criteria supplier selection may be in relation to (i) a decision maker’s ambiguous preferences, such as the importance between criteria, ii) the suppliers’ supply capacities of, and demand for, different items, and (iii) known information about suppliers with respect to the set of criteria, such as each supplier’s delivery times or their average defect ratios. Whilst previous work has explored the first two of these, less work has explored uncertainty pertaining to information about suppliers in terms of the criteria and, specifically, how it could be efficiently reduced. Such uncertainty is an important problem to address, as it may have a large impact upon an order regarding its perceived quality compared to its realised quality, so reducing such uncertainty can have a significant impact.
Uncertainty within multi-criteria supplier selection may be in relation to (i) a decision maker’s ambiguous preferences, such as the importance between criteria, ii) the suppliers’ supply capacities of, and demand for, different items, and (iii) known information about suppliers with respect to the set of criteria, such as each supplier’s delivery times or their average defect ratios. Whilst previous work has explored the first two of these, less work has explored uncertainty pertaining to information about suppliers in terms of the criteria and, specifically, how it could be efficiently reduced. Such uncertainty is an important problem to address, as it may have a large impact upon an order regarding its perceived quality compared to its realised quality, so reducing such uncertainty can have a significant impact.
Original language | English |
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Pages (from-to) | 113583 |
Journal | Expert Systems with Applications |
Early online date | 23 May 2020 |
DOIs | |
Publication status | Published - 2020 |
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Dive into the research topics of 'Targeted Evidence Collection for Uncertain Supplier Selection'. Together they form a unique fingerprint.Projects
- 1 Finished
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Value Added Data Systems: Principles and Architecture.
Paton, N. (PI), Fernandes, A. (CoI) & Keane, J. (CoI)
1/04/15 → 30/09/20
Project: Research