Name
Abstract | ||
|---|---|---|
Managers of large industrial projects often measure performance by multiple attributes. In previous work, we developed a multiattribute ranking and selection procedure to allow tradeoffs between conflicting objectives. More recent developments in ranking and selection incorporate the notion of "constraints", or "targets", that must be satisfied. In this paper we demonstrate how some forms of single attribute utility functions can be used to create a target or constraint. We re-analyze our original problem under the assumption that there are unacceptable levels for some attributes. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/WSC.2006.323077 | Winter Simulation Conference |
Keywords | Field | DocType |
large industrial project,single attribute utility function,conflicting objective,multiattribute ranking,multiple attribute,original problem,recent development,previous work,unacceptable level,selection procedure,utility theory,satisfiability | Data mining,Ranking,Systems engineering,Computer science,Artificial intelligence,Machine learning,Utility theory | Conference |
ISBN | Citations | PageRank |
1-4244-0501-7 | 19 | 1.02 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Douglas J. Morrice | 1 | 538 | 116.21 |
| John C. Butler | 2 | 179 | 21.20 |