Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP model populated with data, the ANP model having feedback connections in place among nodes within the ANP model, and a processor in communication with the ANP storage memory. The processor is configured to facilitate selecting one or more metrics to use to determine influence of criteria within the ANP model. Also, the processor determines a combined influence score, the combined influence score being a single score for each of the criteria in the ANP model. Also, the processor determines which of the criteria in the ANP model is most influential among the criteria in the ANP model, for the one or more metric which is selected to use to determine the influence of the nodes in the ANP model.

Abstract: An analytic network process (ANP) storage memory stores an ANP weighted supermatrix representing an ANP model. A processor is in communication with the ANP storage memory. The processor is configured to change priorities of a node in the ANP weighted supermatrix to be more important, to change priorities of the node in the ANP weighted supermatrix to be less important, and to assess a sensitivity of the node which was changed relative to the ANP model. The processor further is configured to maintain a same proportionality in the ANP weighted supermatrix for the changing of the priorities and the assessing of the relative sensitivity.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory. The processor is configured to facilitate measuring how alternatives synthesize with respect to a fixed node in the stored ANP weighted supermatrix to determine a perspective metric vector for the fixed node. Also, the processor maintains a same proportionality in the stored ANP weighted supermatrix for the measuring of the perspective metric vector for the fixed node.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory. The processor is configured to facilitate measuring an instantaneous rate of change of alternative scores with respect to a fixed node of the ANP model, to determine a marginal influence of the fixed node. Also, the processor is configured to facilitate maintaining a same proportionality in the stored ANP weighted supermatrix as an importance of the fixed node is changed to measure the instantaneous rate of change.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP model with feedback connections in place among nodes within the ANP model and with at least preliminary input of data stored in the ANP model, and a processor in communication with the ANP storage memory. The process performs a rank influence analysis on the ANP model, wherein the rank influence analysis determines one or more nodes among the nodes in the ANP model in which a smallest upward or downward change in importance will change a rank among the nodes in the ANP model, so as to determine which one or more nodes have the most influence on the rank among the nodes in the ANP model.

Abstract: A computer-implemented system is provided for an analytic network process (ANP) control structure with feedback throughout the ANP control structure. The computer-implemented system includes an ANP control structure storage unit that stores an ANP control structure with feedback throughout the ANP control structure. Also included is a synthesizer that performs a BOCR calculation on the ANP control structure with feedback throughout the ANP control structure, to yield a result which is proper according to ANP theory when values are non-trivial. Also disclosed is a computer-implemented method for an analytic network process (ANP) control structure with feedback through the ANP control structure, and a related computer-readable storage medium encoded with a computer program.

Abstract: An analytic network process (ANP) storage memory stores an ANP weighted supermatrix representing an ANP model. A processor is in communication with the ANP storage memory. The processor fixes each one of plural nodes one at a time in the ANP model and measures a row sensitivity of each of the nodes as it is fixed, the row sensitivity being measured using one or both of (i) a predetermined increase value and (ii) a predetermined decrease value. Also, it scores how much synthesized alternatives scores found by doing ANP row sensitivity on each of the fixed nodes change from original values thereof, to generate a value indicating a change distance for each of the nodes. A same proportionality is maintained in the stored ANP weighted supermatrix as the fixed node is changed by the predetermined increase and/or decrease values.

Abstract: An analytic network process (ANP) storage memory stores an ANP weighted supermatrix representing an ANP model. A processor is in communication with the ANP storage memory. The processor is configured to change priorities of a node in the ANP weighted supermatrix to be more important, to change priorities of the node in the ANP weighted supermatrix to be less important, and to assess a sensitivity of the node which was changed relative to the ANP model. The processor further is configured to maintain a same proportionality in the ANP weighted supermatrix for the changing of the priorities and the assessing of the relative sensitivity.

Abstract: A computer-implemented system is provided for an analytic network process (ANP) control structure with feedback throughout the ANP control structure. The computer-implemented system includes an ANP control structure storage unit that stores an ANP control structure with feedback throughout the ANP control structure. Also included is a synthesizer that performs a BOCR calculation on the ANP control structure with feedback throughout the ANP control structure, to yield a result which is proper according to ANP theory when values are non-trivial. Also disclosed is a computer-implemented method for an analytic network process (ANP) control structure with feedback through the ANP control structure, and a related computer-readable storage medium encoded with a computer program.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory. The processor is configured to facilitate measuring an instantaneous rate of change of alternative scores with respect to a fixed node of the ANP model, to determine a marginal influence of the fixed node. Also, the processor is configured to facilitate maintaining a same proportionality in the stored ANP weighted supermatrix as an importance of the fixed node is changed to measure the instantaneous rate of change.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory. The processor is configured to facilitate measuring how alternatives synthesize with respect to a fixed node in the stored ANP weighted supermatrix to determine a perspective metric vector for the fixed node. Also, the processor maintains a same proportionality in the stored ANP weighted supermatrix for the measuring of the perspective metric vector for the fixed node.

Abstract: A computer-implemented system is provided for an analytic network process (ANP) control structure with feedback throughout the ANP control structure. The computer-implemented system includes an ANP control structure storage unit that stores an ANP control structure with feedback throughout the ANP control structure. Also included is a synthesizer that performs a BOCR calculation on the ANP control structure with feedback throughout the ANP control structure, to yield a result which is proper according to ANP theory when values are non-trivial. Also disclosed is a computer-implemented method for an analytic network process (ANP) control structure with feedback through the ANP control structure, and a related computer-readable storage medium encoded with a computer program.