Image-based analytics of supply chain optimization problems
A system and method are disclosed for image analysis of supply chain planning problems modeled as a linear programming (LP) problems. Embodiments include receiving an LP matrix representing constraints and variables of at least a portion of a supply chain planning problem, generating a sorted variable index for the variables of the LP matrix, generating a sorted constraint index for the constraints of the LP matrix, identifying functions of the variables and the constraints, selecting one or more colors of pixels of a supply chain problem image based, at least in part, on the identified functions of the variables and constraints, selecting locations of the pixels, and displaying a visualization of the supply chain problem image.
1. A system of image analysis of planning problems modeled as linear programing (LP) problems, comprising:
a computer, comprising a processor and memory, the computer configured to:
receive an LP matrix representing constraints and variables of at least a portion of a planning problem;
identify functions of the variables and the constraints;
color pixels of a problem image based, at least in part, a link between each pixel and a corresponding individual variable or constraint to determine a color of each pixel;
determine locations of the pixels on the problem image based, at least in part, on a link between each pixel and a column matrix location of a sorted variable index and a row matrix location of a sorted constraint index;
display a visualization of the problem image based on the colored pixels; and
update the visualization of the problem image based on receiving one or more updates to the variables.
2. The system of claim 1 , wherein the computer is further configured to:
refresh the visualization of the problem image based on filtering one or more of the variables and the constraints.
3. The system of claim 1 , wherein the computer is further configured to:
color pixels based on a value of row-column coefficients of the LP matrix satisfying one or more threshold values.
4. The system of claim 3 , wherein the one or more threshold values indicate a minimum, a maximum, or a range.
5. The system of claim 3 , wherein the computer is further configured to:
receive one or more threshold changes comprising one or more modifications to the one or more threshold values; and
in response to receiving the one or more threshold changes, update the problem image by removing, adding, or differently coloring pixels.
6. The system of claim 1 , wherein the computer is further configured to:
determine dimensions of the problem image based on a total number of variables and constraints in the LP matrix.
7. The system of claim 1 , wherein the color of each pixel indicates domain and categorization of elements of the problem image.
8. A computer-implemented method of image analysis of planning problems modeled as linear programing (LP) problems, comprising:
receiving an LP matrix representing constraints and variables of at least a portion of a planning problem;
identifying functions of the variables and the constraints;
coloring pixels of a problem image based, at least in part, a link between each pixel and a corresponding individual variable or constraint to determine a color of each pixel;
determining locations of the pixels on the problem image based, at least in part, on a link between each pixel and a column matrix location of a sorted variable index and a row matrix location of a sorted constraint index;
displaying a visualization of the problem image based on the colored pixels; and
updating the visualization of the problem image based on receiving one or more updates to the variables.
9. The computer-implemented method of claim 8 , further comprising:
refreshing the visualization of the problem image based on filtering one or more of the variables and the constraints.
10. The computer-implemented method of claim 8 , further comprising:
coloring pixels based on a value of row-column coefficients of the LP matrix satisfying one or more threshold values.
11. The computer-implemented method of claim 10 , wherein the one or more threshold values indicate a minimum, a maximum, or a range.
12. The computer-implemented method of claim 10 , further comprising:
receiving one or more threshold changes comprising one or more modifications to the one or more threshold values; and
in response to receiving the one or more threshold changes, updating the problem image by removing, adding, or differently coloring pixels.
13. The computer-implemented method of claim 8 , further comprising:
determining dimensions of the problem image based on a total number of variables and constraints in the LP matrix.
14. The computer-implemented method of claim 8 , wherein the color of each pixel indicates domain and categorization of elements of the problem image.
15. A non-transitory computer-readable medium embodied with software providing image analysis of planning problems modeled as linear programing (LP) problems, the software when executed:
receives an LP matrix representing constraints and variables of at least a portion of a planning problem;
identifies functions of the variables and the constraints;
colors pixels of a problem image based, at least in part, on a link between each pixel and a corresponding individual variable or constraint to determine a color of each pixel;
determines locations of the pixels on the problem image based, at least in part, on a link between each pixel and a column matrix location of a sorted variable index and a row matrix location of a sorted constraint index;
displays a visualization of the problem image based on the colored pixels; and
updates the visualization of the problem image based on receiving one or more updates to the variables.
16. The non-transitory computer-readable medium of claim 15 , wherein the software when executed further:
refreshes the visualization of the problem image based on filtering one or more of the variables and the constraints.
17. The non-transitory computer-readable medium of claim 15 , wherein the software when executed further:
colors pixels based on a value of row-column coefficients of the LP matrix satisfying one or more threshold values.
18. The non-transitory computer-readable medium of claim 17 , wherein the one or more threshold values indicate a minimum, a maximum, or a range.
19. The non-transitory computer-readable medium of claim 17 wherein the software when executed further:
receives one or more threshold changes comprising one or more modifications to the one or more threshold values; and
in response to receiving the one or more threshold changes, updates the problem image by removing, adding, or differently coloring pixels.
20. The non-transitory computer-readable medium of claim 15 , wherein the software when executed further:
determines dimensions of the problem image based on a total number of variables and constraints in the LP matrix.