Journal
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Volume 48, Issue 5, Pages 1092-1105Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2016.1239140
Keywords
Multiple attribute decision-making; partitioned Bonferroni mean; partitioned geometric Bonferroni mean; intuitionistic uncertain linguistic
Categories
Funding
- National Natural Science Foundation of China [71271124, 71471172, 61571272]
- Humanities and Social Sciences Research Project of Ministry of Education of China [13YJC630104]
- Shandong Provincial Natural Science Foundation [ZR2013GQ011]
- Project of Shandong Province Higher Educational Science and Technology Program [J15LN56, J16LN25]
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The Bonferroni mean (BM) was originally introduced by Bonferroni and generalised by many other researchers due to its capacity to capture the interrelationship between input arguments. Nevertheless, in many situations, interrelationships do not always exist between all of the attributes. Attributes can be partitioned into several different categories and members of intra-partition are interrelated while no interrelationship exists between attributes of different partitions. In this paper, as complements to the existing generalisations of BM, we investigate the partitioned Bonferroni mean (PBM) under intuitionistic uncertain linguistic environments and develop two linguistic aggregation operators: intuitionistic uncertain linguistic partitioned Bonferroni mean (IULPBM) and its weighted form (WIULPBM). Then, motivated by the ideal of geometric mean and PBM, we further present the partitioned geometric Bonferroni mean (PGBM) and develop two linguistic geometric aggregation operators: intuitionistic uncertain linguistic partitioned geometric Bonferroni mean (IULPGBM) and its weighted form (WIULPGBM). Some properties and special cases of these proposed operators are also investigated and discussed in detail. Based on these operators, an approach for multiple attribute decision-making problems with intuitionistic uncertain linguistic information is developed. Finally, a practical example is presented to illustrate the developed approach and comparison analyses are conducted with other representative methods to verify the effectiveness and feasibility of the developed approach.
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