Methods, software, products and systems used to support decision making in complex multidimensional problem environments. Methods, software, products and systems to prioritize solutions for selection based upon selection criteria and available data regarding the possible solutions. The methods achieve a robust approach to determine the sensitivity of a selection to a multi-parameter profile of selection criteria and the importance of such criteria.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method executed on a computer for an analysis of data, comprising the steps of: providing a computer having a memory and a processing unit adapted to run computer readable program code means; providing to said memory an original selection profile comprising an at least one selection criteria for an at least one property; each respective item of a plurality of items comprises said at least one property; providing to said memory a data from a data set comprising said plurality of items, said data having at least one property value of said at least one property for at least one item of said plurality of items and an at least one uncertainty value for said at least one property value of at least one item of said plurality of items; each respective item of said plurality of items comprises at least one score; each of said at least one score comprises an uncertainty; said computer running a computer readable program code means processing said original selection profile and processing said data and calculating an original score for each respective item of said plurality of items and an original uncertainty in each original score; said computer processing a criterion of said selection criteria of said original selection profile: a. said computer executing a computer readable program code means calculating a sensitivity of said criterion resulting from a perturbation of said criterion by executing the steps of: i. running a computer readable program code means to generate a new selection profile resulting from a perturbation of said criterion in said original selection profile; ii. running a computer readable program code means processing said new selection profile and processing said data and calculating a new score for each respective item of said plurality of items and a new uncertainty in each new score; iii. running a computer readable program code means processing said original scores and new scores for said plurality of items and processing the original uncertainties in the original scores and new uncertainties in the new scores in calculating a sensitivity value for said perturbation to said criterion; b. said computer running a computer readable program code means repeating steps (i), (ii) and (iii) for one or a plurality of said perturbation of said criterion; c. said computer running a computer readable program code means to calculate a sensitivity value for said criterion; said computer running a computer readable program code means repeating steps (a), (b) and (c) for at least a second criterion in said selection profile different from said criterion; said computer providing an output comprising at least one of said sensitivity value for said criterion or said sensitivity value for said second criterion. 2. Method of claim 1, in which the original selection profile is a multi-dimensional desirability function. 3. The method of claim 1, in which the step of providing to said memory an original selection profile, further comprises providing an importance value for at least one selection criteria in said original scoring profile and further comprising the steps: said computer processing an importance value of a criterion of said selection criteria in said original selection profile: d. said computer executing a computer readable program code means calculating a sensitivity of said importance value of said criterion resulting from a perturbation of said importance value of said criterion by executing the steps of: iv. running a computer readable program code means to generate a new selection profile resulting from a perturbation of said importance value of said criterion in said original selection profile; v. running a computer readable program code means processing said new selection profile and processing said data and calculating a new score for each respective item of said plurality of items and a new uncertainty in each new score; vi. running a computer readable program code means processing said original scores and new scores for said plurality of items and processing the original uncertainties in the original scores and the new uncertainties in the new scores in calculating a sensitivity value for said perturbation to said importance value of said criterion, e. said computer running a computer readable program code means repeating steps (iv), (v) and (vi) for one or a plurality of said perturbation of said importance value; f. said computer running a computer readable program code means to calculate a sensitivity value for said importance value; said computer running a computer readable program code means repeating steps (d), (e) and (f) for at least a second importance value in said selection profile different from said importance value; said computer providing an output comprising at least one of said sensitivity value for said importance value, or said sensitivity value for said second importance value. 4. The method of claim 3, in which the original selection profile is a multi-dimensional desirability function. 5. The method of claim 2, in which the original selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∑ i = 1 M   c i  d i  ( x i ) 6. The method of claim 2, in which the original selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = 1 ∑ i = 1 M   c i  ∑ i = 1 M   c i  d i  ( x i ) 7. Method of claim 2, in which the original selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∏ i = 1 M   d i  ( x i ) c i 8. The method of claim 2, in which the original selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∑ i = 1 M   c i  ∏ i = 1 M   d i  ( x i ) c i 9. The method of claim 4, in which the original selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∏ i = 1 M   d i  ( x i ) c i 10. The method of claim 2, further comprising the optional step of receiving an input in the computer memory specifying a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−r({sj},{s′j}) in which r is the correlation coefficient of the original scores, sj, new scores, sj′, of one or a plurality of K items in the data set. 11. The method of claim 2, further comprising the optional step of receiving an input in the computer memory specifying a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−ρ({rj},{r′j}) in which ρ is the Spearman's rank correlation coefficient of the original ranks, rj, and new ranks, rj′, of one or a plurality of K items in the data set. 12. The method of claim 2, further comprising the optional step of receiving an input in the computer memory specifying a level of significance and the optional step of receiving an input in the computer memory specifying a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−ρ({rj},{r′j}) in which ρ is the Spearman's rank correlation coefficient, modified to reflect when the perturbation results in a statistically significant change in the item scores, of the original ranks, rj, and new ranks, rj′, of one or a plurality of K items in the data set. 13. Method of claim 4, further comprising the optional step of receiving an input in the computer memory specifying a level of significance and the optional step of receiving an input in the computer memory specifying a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−ρ({rj},{r′j}) in which ρ is the Spearman's rank correlation coefficient, modified to reflect when the perturbation results in a statistically significant change in the item scores, of the original ranks, rj, and new ranks, rj′, of one or a plurality of K items in the data set. 14. The method of claim 2, in which the original scores and new scores for said plurality of items are calculated by processing the expected value of the multi-dimensional desirability function. 15. The method of claim 2, in which the probability distribution for the original score and new score for said item can be assumed to be normally distributed with a mean resulting from processing the expected value of the multi-dimensional desirability function and variance resulting from processing the variance of the multi-dimensional desirability function. 16. The method of claim 4, in which the probability distribution for the original score and new score for said item can be assumed to be normally distributed with mean resulting from processing the expected value of the multi-dimensional desirability function and variance resulting from processing the variance of the multi-dimensional desirability function. 17. The method of claim 2, in which in step (a) the perturbation to said criterion of said property in said selection profile is a rigid shift, Δxk, of the desirability function of said criterion for said property and the new selection profile is the multi-dimensional desirability function D(x1,x2, . . . ,xM|d1(x1),d2(x2), . . . dk(xk+Δxk), . . . ,dM(xM),c1,c2, . . . ,cM) in which D is the multi-dimensional desirability function defining to the original selection profile. 18. The method of claim 4, in which in step (a) the perturbation to said criterion of said property in said selection profile is a rigid shift, Δxk, of the desirability function of said criterion for said property and the new selection profile is the multi-dimensional desirability function D(x1,x2, . . . ,xM|d1(x1),d2(x2), . . . dk(xk+Δxk), . . . ,dM(xM),c1,c2, . . . ,cM) in which D is the multi-dimensional desirability function defining to the original selection profile. 19. The method of claim 4, in which in step (d) said perturbation of said importance value of said criterion is a shift in importance, Δck, in a coefficient defining the importance of said criterion for said property and the new selection profile is a multi-dimensional desirability function of the form D(x1j,x2j, . . . ,xM|d1(x1),d2(x2), . . . ,dM(xM),c1,c2, . . . ck+Δck, . . . ,cM). in which D is the multi-dimensional desirability function defining the original selection profile. 20. The method of claim 4, in which in step (d) said perturbation of said importance value of said criterion is a perturbation, Δdk, of the desirability function of said criterion for said property and the new selection profile is a multi-dimensional desirability function comprising: D(x1j,x2j, . . . ,xM|d1(x1),d2(x2), . . . ,d′k(xk), . . . ,dM(xM)) in which D is the multi-dimensional desirability function defining the original selection profile and d k ′  ( x k ) = ( d k  ( x k ) - min  ( d k  ( x ) ) )  ( 1 - Δ   d k max  ( d k  ( x ) ) - min  ( d k  ( x ) ) ) + Δ   d k + min  ( d k  ( x ) ) 21. A computer program product for an analysis of data, comprising: a computer readable program code means which provides to a computer memory an original selection profile comprising an at least one selection criteria for an at least one property; each respective item of a plurality of items comprises said at least one property; a computer readable program code means which provides to said memory a data from a data set comprising said plurality of items, said data having at least one property value of said at least one property for at least one item of said plurality of items and an at least one uncertainty value for said at least one property value of at least one item of said plurality of items; each respective item of said plurality of items comprises at least one score, and in which each of said at least one score comprises an uncertainty; a computer readable program code means which processes said original selection profile and processes said data set and is adapted to calculate an original score for each respective item of said plurality of items and an original uncertainty in each original score; a computer readable program code means which processes a criterion of said selection criteria of said original selection profile: a. a computer readable program code means which calculates a sensitivity of said criterion resulting from a perturbation of said criterion which comprises: i. a computer readable program code means which generates a new selection profile resulting from a perturbation of said criterion in said original selection profile; ii. a computer readable program code means which processes said new selection profile and processes said data set and which is adapted to calculate a new score for each respective item of said plurality of items and a new uncertainty in each new score; iii. a computer readable program code means which processes said original scores and new scores for said plurality of items and processes the original uncertainties in the original scores and new uncertainties in the new scores and is adapted to calculate a sensitivity value for said perturbation to said criterion; b. a computer readable program code means which is adapted to execute the computer readable program code means (i), (ii) and (iii) for one or a plurality of said perturbation of said criterion; c. a computer readable program code means which is adapted to calculate a sensitivity value for said criterion; a computer readable program code means adapted to execute the computer readable program code means (a), (b) and (c) for at least a second criterion in said selection profile different from said criterion; a computer readable program code means adapted to provide an output comprising at least one of said sensitivity value for said criterion or said sensitivity value for said second criterion. 22. The computer program product of claim 21, in which the original selection profile is a multi-dimensional desirability function. 23. The computer program product of claim 21, further comprising: a computer readable program code means which provides an importance value for at least one selection criteria in said original scoring profile; a computer readable program code means adapted to process said importance value of a criterion of said selection criteria in said original selection profile: d. a computer readable program code means which calculates a sensitivity of said importance value of said criterion resulting from a perturbation of said importance value of said criterion by executing the steps of: iv. a computer readable program code means which can generate a new selection profile resulting from a perturbation of said importance value of said criterion in said original selection profile; v. a computer readable program code means which can process said new selection profile and which is adapted to process said data set and to calculate a new score for each respective item of said plurality of items and to calculate a new uncertainty in each new score; vi. a computer readable program code means which can process said original scores and said new scores for said plurality of items and which is adapted to process the original uncertainties in the original scores and to process the new uncertainties in the new scores to calculate a sensitivity value for said perturbation to said importance value of said criterion, e. a computer readable program code means adapted to execute the computer readable program code means of (iv), (v) and (vi) for one or a plurality of said perturbation of said importance value; f. a computer readable program code means which is adapted to calculate a sensitivity value for said importance value; a computer readable program code means which is adapted to repeat the calculations of (d), (e) and (f) for at least a second importance value in said selection profile different from said importance value; a computer readable program code means which is adapted to provide an output comprising at least one of said sensitivity value for said importance value, or said sensitivity value for said second importance value. 24. The computer program product of claim 23, in which the original selection profile is a multi-dimensional desirability function. 25. The computer program product of claim 22, in which the selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∏ i = 1 M   d i  ( x i ) c i 26. The computer program product of claim 24, in which the selection profile is a multi-dimensional desirability function comprising: D  ( x 1 , x 2 , …  , x M | d 1  ( x 1 ) , d 2  ( x 2 ) , …  , d M  ( x M ) , c 1 , c 2 , …  , c M ) = ∏ i = 1 M   d i  ( x i ) c i 27. The computer program product of claim 22, further adapted to receive an input in the computer memory specifying a level of significance and to receive an input in the computer memory which specifies a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−ρ({rj},{r′j}) in which ρ is the Spearman's rank correlation coefficient, modified to reflect when the perturbation results in a statistically significant change in the item scores, of the original ranks, rj, and new ranks, rj′, of one or a plurality of K items in the data set; in which K has a value in a range of from 1 to the total number of items in the data set. 28. The computer program product of claim 24, further adapted to receive an input in the computer memory specifying a level of significance and to receive an input in the computer memory specifying a proportion of the data set to be selected, K, and in which the sensitivity of said criterion resulting from a perturbation is calculated as 1−ρ({rj},{r′j}) in which ρ is the Spearman's rank correlation coefficient, modified to reflect when the perturbation results in a statistically significant change in the item scores, of the original ranks, rj, and new ranks, rj′, of one or a plurality of K items in the data set; in which K has a value from 1 to the total number of items in the data set. 29. The computer program product of claim 22, in which the probability distribution for the original score and new score for said item can be assumed to be normally distributed with a mean resulting from processing the expected value of the multi-dimensional desirability function and variance resulting from processing the variance of the multi-dimensional desirability function. 30. The computer program product of claim 24, in which the probability distribution for the original score and new score for said one or a plurality of said item can be assumed to be normally distributed with a mean resulting from processing the expected value of the multi-dimensional desirability function and variance resulting from processing the variance of the multi-dimensional desirability function. 31. The computer program product of claim 22, in which the calculation (a) the perturbation to said criterion of said property in said selection profile is a rigid shift, Δxk, of the desirability function of said criterion for said property and the new selection profile is the multi-dimensional desirability function D(x1,x2, . . . ,xM|d1(x1),d2(x2), . . . dk(xk+Δxk), . . . ,dM(xM),c1,c2, . . . ,cM) in which D is the multi-dimensional desirability function which defines the original selection profile. 32. The computer program product of claim 24, in which in the calculation (d) said perturbation of said importance value of said criterion is a shift in importance, Δck, a coefficient defining the importance of said criterion for said property and the new selection profile is a multi-dimensional desirability function comprising D(x1j,x2j, . . . ,xM|d1(x1),d2(x2), . . . ,dM(xM),c1,c2, . . . ,ck+Δck, . . . ,cM). in which D is the multi-dimensional desirability function defining the original selection profile. 33. The computer program product of claim 24, in which in the calculation (d) said perturbation of said importance value of said criterion is a perturbation, Δdk, of the desirability function of said criterion for said property and the new selection profile is a multi-dimensional desirability function comprising: D(x1j,x2j, . . . xM|d1(x1),d2(x2), . . . ,d′k(xk), . . . dM(xM)) in which D is the multi-dimensional desirability function which defines the original selection profile and d k ′  ( x k ) = ( d k  ( x k ) - min  ( d k  ( x ) ) )  ( 1 - Δ   d k max  ( d k  ( x ) ) - min  ( d k  ( x ) ) ) + Δ   d k + min  ( d k  ( x ) ) 34. A method executed on a computer for an analysis of data, comprising the steps of: providing a computer having a memory and a processing unit adapted to run computer readable program code means; providing to said memory an original selection profile comprising an at least one selection criteria for an at least one property; each respective compound of a plurality of compounds comprises said at least one property; providing to said memory a data from a data set comprising said plurality of compounds, said data having at least one property value of said at least one property for at least one compound of said plurality of compounds and an at least one uncertainty value for said at least one property value of at least one compound of said plurality of compounds; each respective compound of said plurality of compounds comprises at least one score; each of said at least one score comprises an uncertainty; said computer running a computer readable program code means processing said original selection profile and processing said data and calculating an original score for each respective compound of said plurality of compounds and an original uncertainty in each original score; said computer processing a criterion of said selection criteria of said original selection profile: A. said computer executing a computer readable program code means calculating a sensitivity of said criterion resulting from a perturbation of said criterion by executing the steps of: I. running a computer readable program code means to generate a new selection profile resulting from a perturbation of said criterion in said original selection profile; II. running a computer readable program code means processing said new selection profile and processing said data and calculating a new score for each respective compound of said plurality of compounds and a new uncertainty in each new score; III. running a computer readable program code means processing said original scores and new scores for said plurality of compounds and processing the original uncertainties in the original scores and new uncertainties in the new scores in calculating a sensitivity value for said perturbation to said criterion; B. said computer running a computer readable program code means repeating steps (I), (II) and (III) for one or a plurality of said perturbation of said criterion; C. said computer running a computer readable program code means to calculate a sensitivity value for said criterion; said computer running a computer readable program code means repeating steps (A), (B) and (C) for at least a second criterion in said selection profile different from said criterion; said computer providing an output comprising at least one of said sensitivity value for said criterion or said sensitivity value for said second criterion. 35. The method of claim 34, in which the step of providing to said memory an original selection profile, further comprises providing an importance value for at least one selection criteria in said original scoring profile and further comprising the steps: said computer processing an importance value of a criterion of said selection criteria in said original selection profile: D. said computer executing a computer readable program code means calculating a sensitivity of said importance value of said criterion resulting from a perturbation of said importance value of said criterion by executing the steps of: IV. running a computer readable program code means to generate a new selection profile resulting from a perturbation of said importance value of said criterion in said original selection profile; V. running a computer readable program code means processing said new selection profile and processing said data and calculating a new score for each respective item of said plurality of compounds and a new uncertainty in each new score; VI. running a computer readable program code means processing said original scores and new scores for said plurality of compounds and processing the original uncertainties in the original scores and new uncertainties in the new scores in calculating a sensitivity value for said perturbation to said importance value of said criterion, E. said computer running a computer readable program code means repeating steps (IV), (V) and (VI) for one or a plurality of said perturbation of said importance value; F. said computer running a computer readable program code means to calculate a sensitivity value for said importance value; said computer running a computer readable program code means repeating steps (D), (E) and (F) for at least a second importance value in said selection profile different from said importance value; said computer providing an output comprising at least one of said sensitivity value for said importance value, or said sensitivity value for said second importance value. 36. The method of claim 1, wherein said plurality of items is a plurality of compounds. 37. The method of claim 1, wherein said plurality of items is a plurality of candidate drugs. 38. The method of claim 3, wherein said importance value is an importance value for a criterion of a property of a compound. 39. The computer program product of claim 21, wherein said item is a compound. 40. The computer program product of claim 21, wherein said item is a candidate drug. 41. The computer program product of claim 23, wherein said importance value is an importance value for a criterion of a compound. 42. The method of claim 34, wherein said plurality of items is a plurality of organic compounds. 43. The method of claim 34, wherein said plurality of items is a plurality of candidate drugs. 44. The method of claim 34, wherein said uncertainty value is an uncertainty value for a property of a candidate drug.