Method and system for connecting analytic network process model (ANP) with feedback throughout the ANP model between sub-networks

• US 8,341,103 B2
• Filed: 07/24/2009
• Issued: 12/25/2012
• Est. Priority Date: 07/24/2009
• Status: Expired due to Fees

• Current Assignee: Decision Lens, Inc.
• Original Assignee: Decision Lens, Inc.
• Inventors: Adams, William James Louis, Saaty, Daniel Lowell
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): CHANG, LI WU
• Application Number:
  US12/508,703
• Publication Number:
  US 20110022556A1
• Time in Patent Office: 1,250 Days
• Field of Search: None
• US Class Current: 706/46
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

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.

Claims

1. A computer-implemented system for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

a memory configured to store an ANP control structure; and

a processor cooperatively operable with the memory, the processor configured to;

store, in the memory, the ANP control structure with feedback throughout the ANP control structure;

perform 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; and

store, in the stored ANP control structure, subnetworks according to ANP theory, one of the subnetworks being attached to a node-to-cluster connection in the ANP control structure instead of being attached to the node itself,

the non-trivial values when the result is proper being when non-zero ANP alternatives of invert and add, or positives minus negatives, are under costs or risks in the ANP control structure using a subtraction formula.

2. The system of claim 1, further comprising:

an output unit configured to output, for simultaneous display to a user, more than two contiguous levels of the ANP control structure with feedback between said more than two contiguous levels.

3. The system of claim 1, further comprising:

an output unit configured to output, for a display to a user, a result of the calculations on the ANP control structure with feedback.

4. The system of claim 1, the non-trivial values when the result is proper being when non-0.5 ANP alternatives are under costs or risks in the ANP control structure using a probabilistic formula.

5. The system of claim 1, further comprising

an input unit configured to input, from an input device, pairwise comparisons, ANP ratings, or ANP client data, which are transformed into priority vectors and stored into the ANP control structure representing, the pairwise comparisons representing a user'"'"'s judgment of priority between the ANP alternatives in the pair, the ANP ratings representing a user'"'"'s rating of a choice, and the ANP client data representing real world values.

6. A computer-implemented system for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

an ANP control structure storage unit that stores an ANP control structure with feedback throughout the ANP control structure;

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;

an input unit configured to input, from an input device, pairwise comparisons for pairs of ANP alternatives into the stored ANP control structure representing, the pairwise comparisons representing a user'"'"'s judgment of priority between the ANP alternatives in the pair; and

an output unit configured to output, for a display to a user, more than two contiguous levels of the ANP control structure with feedback,

the stored ANP control structure being configured to include subnetworks according to ANP theory, one of the subnetworks being attached to a node-to-cluster connection in the ANP control structure stored in the ANP control structure storage unit instead of being attached to the node itself,

the non-trivial values when the result is proper being when (i) non-zero ANP alternatives of invert and add, or positives minus negatives, are under costs or risks in the ANP control structure using a subtraction formula, or (ii) non-0.5 ANP alternatives are under costs or risks in the ANP control structure using a probabilistic formula.

7. A computer-implemented method for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer of a computer processor, 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,

the stored ANP control structure being configured to include subnetworks according to ANP theory, one of the subnetworks being attached to a node-to-cluster connection in the ANP control structure stored in the ANP control structure storage unit instead of being attached to the node itself,

the non-trivial values when the result is proper being when non-zero ANP alternatives of invert and add, or positives minus negatives, are under costs or risks in the ANP control structure using a subtraction formula.

8. The method of claim 7, further comprising:

outputting, from an output unit, for a display to a user, more than two contiguous levels of the ANP control structure with feedback between said more than two contiguous levels.

9. The method of claim 7, further comprising:

outputting, from an output unit, for a display to a user, a result of the calculations on the ANP control structure with feedback.

10. The method of claim 7, the non-trivial values when the result is proper being when non-0.5 ANP alternatives are under costs or risks in the ANP control structure using a probabilistic formula.

11. The method of claim 7, further comprising inputting, from an input device, pairwise comparisons, ANP ratings, or ANP client data, which are transformed into priority vectors and stored into the ANP control structure representing, the pairwise comparisons representing a user'"'"'s judgment of priority between the ANP alternatives in the pair, the ANP ratings representing a user'"'"'s rating of a choice, and the ANP client data representing real world values.

12. A non-transitory computer-readable storage medium encoded with a computer program for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, wherein execution of said computer program by one or more processors causes said one or more processors to perform the steps of:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer, 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,

the stored ANP control structure being configured to include subnetworks according to ANP theory, one of the subnetworks being attached to a node-to-cluster connection in the ANP control structure stored in the ANP control structure storage unit instead of being attached to the node itself,

the non-trivial values when the result is proper being when (i) non-zero ANP alternatives of invert and add, or positives minus negatives, are under costs or risks in the ANP control structure using a subtraction formula.

13. The non-transitory computer-readable storage medium of claim 12, further comprising instructions for:

outputting, from an output unit, for a display to a user, more than two contiguous levels of the ANP control structure with feedback between said more than two contiguous levels.

14. The non-transitory computer-readable storage medium of claim 12, further comprising instructions for:

outputting, from an output unit, for a display to a user, a result of the calculations on the ANP control structure with feedback.

15. The non-transitory computer-readable storage medium of claim 12, the non-trivial values when the result is proper being when non-0.5 ANP alternatives are under costs or risks in the ANP control structure using a probabilistic formula.

16. The non-transitory computer-readable storage medium of claim 12, further comprising instructions for inputting, from an input device, pairwise comparisons, ANP ratings, or ANP client data, which are transformed into priority vectors and stored into the ANP control structure representing, the pairwise comparisons representing a user'"'"'s judgment of priority between the ANP alternatives in the pair, the ANP ratings representing a user'"'"'s rating of a choice, and the ANP client data representing real world values.

17. A computer-implemented system for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

a memory configured to store an ANP control structure; and

a processor cooperatively operable with the memory, the processor configured to;

store, in the memory, the ANP control structure with feedback throughout the ANP control structure; and

perform 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^(k+1)

as c ranges over clusters in the ANP control structure, consistent with the formula;

r_n,c^(k+1)=S_n,c(p_n,c, {tilde over (m)}_c^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

p is a priority vector, and

S_n,c is a synthesizer with respect to connection between cluster c and node n.

18. A computer-implemented system for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

a memory configured to store an ANP control structure; and

a processor cooperatively operable with the memory, the processor configured to;

store, in the memory, the ANP control structure with feedback throughout the ANP control structure; and

perform 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^(k+1)

as c ranges over clusters in the ANP control structure, wherein;

columns of {tilde over (m)}_c^(k) are found by applying an inverter to each column of m_c^(k),an i^th column being

{tilde over (m)}_c,i^(k)=I_n,c,i(m_c,i^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

S_n,c is a synthesizer with respect to connection between cluster c and node n, and

I_n,c,I is the inverter formula for criteria i when using synthesizer S_n,c.

19. A computer-implemented system for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

a memory configured to store an ANP control structure; and

a processor cooperatively operable with the memory, the processor configured to;

store, in the memory, the ANP control structure with feedback throughout the ANP control structure; and

perform 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,

wherein the BOCR calculation is performed consistent with at least one of the following calculations;

calculate

m_n^(k+1)=S_c(p_c, {tilde over (r)}_n^(k+1))

columns of {tilde over (r)}^(k+1) being found by applying an inverter to columns of r^(k), the i^th column being

{tilde over (r)}_n,i^(k+1)=I_c,i(r_n,i^(k+1))

where

m is a supermatrix

r is a column

c is an index of a cluster

n is an index of a node

k is an iteration of synthesis

p is a priority vector

S_c is a synthesizer with respect to cluster c

I_c,i is an inverter formula for cluster i when using synthesizer S_c.

20. A computer-implemented method for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer of a computer processor, 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^(k+1)

as c ranges over clusters in the ANP control structure, consistent with the formula;

r_n,c^(k+1)=S_n,c(p_n,c, {tilde over (m)}_c^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

p is a priority vector, and

S_n,c is a synthesizer with respect to connection between cluster c and node n.

21. A computer-implemented method for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer of a computer processor, 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^(k+1)

as c ranges over clusters in the ANP control structure, wherein;

columns of {tilde over (m)}_c^(k) are found by applying an inverter to each column of m_c^(k), an i^th column being

{tilde over (m)}_c,i^(k)=I_n,c,i(m_c,i^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

S_c,n is a synthesizer with respect to connection between cluster c and node n, and

I_n,c,I is the inverter formula for criteria i when using synthesizer S_n,c.

22. A computer-implemented method for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, comprising:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer of a computer processor, 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,

wherein the BOCR calculation is performed consistent with at least one of the following calculations;

calculate

m_n^(k+1)=S_c(p_c, {tilde over (r)}_n^(k+1))

columns of {tilde over (r)}^(k+1) being found by applying an inverter to columns of r^(k), the i^th column being

{tilde over (r)}_n,i(k+1)I_c,i(r_n,i^(k+1))

where

m is a supermatrix

r is a column

c is an index of a cluster

n is an index of a node

k is an iteration of synthesis

p is a priority vector

S_c is a synthesizer with respect to cluster c

I_c,i is an inverter formula for cluster i when using synthesizer S_c.

23. A non-transitory computer-readable storage medium encoded with a computer program for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, wherein execution of said computer program by one or more processors causes said one or more processors to perform the steps of:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer, 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^(k+1)

as c ranges over clusters in the ANP control structure, consistent with the formula;

r_n,c^(k+1)S_n,c(p_n,c{tilde over (m)}_c^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

p is a priority vector, and

S_n,c is a synthesizer with respect to connection between cluster c and node n.

24. A non-transitory computer-readable storage medium encoded with a computer program for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, wherein execution of said computer program by one or more processors causes said one or more processors to perform the steps of:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer, 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,

wherein the BOCR calculation is performed consistent with the following calculation;

calculate

r_n,c^{(k +1)}

as c ranges over clusters in the ANP control structure, wherein;

columns of {tilde over (m)}_c^(k) are found by applying an inverter to each column of m_c^(k), an i^th column being

{tilde over (m)}_c,i^(k)=I_n,c,i(m_c,i^(k))

where

m is a supermatrix,

r is a column,

c is an index of a cluster,

n is an index of a node,

k is an iteration of synthesis,

S_n,c is a synthesizer with respect to connection between cluster c and node n, and

I_n,c,I is the inverter formula for criteria i when using synthesizer S_n,c.

25. A non-transitory computer-readable storage medium encoded with a computer program for an analytic network process (ANP) control structure with feedback throughout the ANP control structure, wherein execution of said computer program by one or more processors causes said one or more processors to perform the steps of:

storing, in an ANP control structure storage unit, an ANP control structure with feedback throughout the ANP control structure; and

performing, in a synthesizer, 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,

wherein the BOCR calculation is performed consistent with at least one of the following calculations;

calculate

m_n^(k+1)=S_c(i p_c, {tilde over (r)}_n^{( k+1)})

columns of {tilde over (r)}^(k+1) being found by applying an inverter to columns of r^(k), the i^th column being

{tilde over (r)}_n,i^(k+1)=I_c,i(r_n,i^(k+1))

where

m is a supermatrix

r is a column

c is an index of a cluster

n is an index of a node

k is an iteration of synthesis

p is a priority vector

S_c is a synthesizer with respect to cluster c

I_c,i is an inverter formula for cluster i when using synthesizer S_c.