Title
How to treat strict preference information in multicriteria decision analysis.
Abstract
This paper addresses the use of incomplete information on both multi-criteria alternative values and importance weights in evaluating decision alternatives. Incomplete information frequently takes the form of strict inequalities, such as strict orders and strict bounds. En route to prioritizing alternatives, the majority of previous studies have replaced these strict inequalities with weak inequalities, by employing a small positive number. As this replacement closes the feasible region of decision parameters, it circumvents certain troubling questions that arise when utilizing a mathematical programming approach to evaluate alternatives. However, there are no hard and fast rules for selecting the factual small value and, even if the choice is possible, the resultant prioritizations depend profoundly on that choice. The method developed herein addresses and overcomes this drawback, and allows for dominance and potential optimality among alternatives, without selecting any small value for the strict preference information. Given strict information on criterion weights alone, we form a linear program and solve it via a two-stage method. When both alternative values and weights are provided in the form of strict inequalities, we first construct a nonlinear program, transform it into a linear programming equivalent, and finally solve this linear program via the same two-stage method. One application of this methodology to a market entry decision, a salient subject in the area of international marketing, is demonstrated in detail herein. Journal of the Operational Research Society (2011) 62, 1771-1783. doi:10.1057/jors.2010.155 Published online 3 November 2010
Year
DOI
Venue
2011
10.1057/jors.2010.155
JORS
Keywords
Field
DocType
communications technology,scheduling,marketing,reliability,management science,information technology,project management,production,incomplete information,operational research,inventory,location,investment,computer science,information systems,linear program,mathematical programming,logistics,forecasting,nonlinear programming,operations research
Drawback,Decision analysis,Information system,Computer science,Information technology,Operations research,Feasible region,Linear programming,Complete information,Management science,Operations management,Project management
Journal
Volume
Issue
ISSN
62
10
0160-5682
Citations 
PageRank 
References 
1
0.35
11
Authors
2
Name
Order
Citations
PageRank
Kyung Sam Park125725.17
I. Jeong210.35