A new method for managing the uncertainties in evaluating multi-person multi-criteria location choices, using a perceptual computer

Shilian Han () and Jerry Mendel ()

Annals of Operations Research, 2012, vol. 195, issue 1, 277-309

Abstract: The international logistics centers choice problem is a very important issue in International logistics. The location choice problem usually involves numbers and words in which all of the criteria are weighted using words and the performance evaluations for all sub-criteria are either numbers or words. How to aggregate all of these data without losing information is a very daunting task using a type-1 fuzzy set (T1 FS) approach. This paper applies a new methodology—Perceptual Computer (Per-C)—to help solve this hierarchical multi-person multi-criteria decision making problem. The Per-C has three components: encoder, computing with words (CWW) engine and decoder. First, the interval approach (IA) is used to obtain interval type-2 fuzzy set (IT2 FS) word models for the words in a pre-specified vocabulary. Second, a linguistic weighted average (LWA) is used to aggregate all the data including numbers and words modeled by IT2 FSs. Finally, a centroid-based ranking method is used to rank the location choices, and a similarity measure is used to obtain similarities of the location choices. The decision-maker decides the winning location choice as the one with the highest ranking and least similarity to other locations. Copyright Springer Science+Business Media, LLC 2012

Keywords: Hierarchical multi-person multi-criteria decision making; Interval type-2 fuzzy set (IT2 FS); Location choices; Perceptual computer (Per-C) (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10479-011-0956-6

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