
This paper presents a new approach to the solution of resource or task allocation problems. A network flow optimization problem is posed that combines binary integer programming methods with fuzzy decision making processes, to obtain optimal solutions to resource allocation problems. In existing resource allocation methods there is a large burden on accurately specifying cost functions associated with tasks that are carried out as flows on arcs through the network. Fuzzy decision theory is utilized to model these objective functions, in order to capture imprecise conditions associated with decision making under constraint feedback information. Efficient programming methods are used to obtain solution sets of optimal binary decision variables.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
