1. A method of determining a plurality of coefficients of an objective function of a mathematical programming model in a computing environment, said method comprising: identifying a plurality of attributes of said model, wherein said plurality of attributes contributes to a goal, wherein said goal is a determination of said plurality of coefficients of said objective function, wherein said goal is included in a top level of a hierarchy having a structure specified by the Analytic Hierarchy Process (AHP), wherein said plurality of attributes is included in a second level of said hierarchy, and wherein said second level is subordinate to said top level in said hierarchy; determining a first set of objective function coefficient values as initially representing said plurality of coefficients of said objective function, wherein said first set of objective function coefficient values specifies a first solution of said model; initializing a prevailing solution to said first solution, wherein said first set of objective function coefficient values determines said prevailing solution; generating multiple sets of objective function coefficient values determining corresponding multiple solutions of said model in addition to said prevailing solution, wherein said generating multiple sets of objective function coefficient values includes sampling a sample space based on said prevailing solution, wherein said multiple solutions are included in a bottom level of said hierarchy, wherein said bottom level is subordinate to said second level, and wherein said hierarchy relates each attribute of said plurality of attributes to said multiple solutions; executing the AHP by a computing system, wherein said executing the AHP includes evaluating said multiple solutions to provide a ranking of said multiple solutions, wherein said ranking of said multiple solutions is dependent upon a pair-wise comparison of said plurality of attributes across said second level of said hierarchy and a plurality of pair-wise comparisons of said multiple solutions across said bottom level of said hierarchy; selecting a second solution of said multiple solutions, wherein said selecting is based on said ranking of said multiple solutions, wherein said second solution is specified by a second set of objective function coefficients; determining that said second solution exceeds a sum of said prevailing solution and a specified tolerance; setting said prevailing solution to said second solution in response to said determining that said second solution exceeds said sum; setting said first set of objective function coefficient values to said second set of objective function coefficient values in response to said determining that said second solution exceeds said sum; subsequent to said determining that said second solution exceeds said sum, said setting said prevailing solution, and said setting said first set of objective function coefficient values, repeating said generating, said executing the AHP, said selecting said second solution, said setting said prevailing solution, and said setting said first set of objective function coefficient values until said second solution does not exceed said sum; determining, subsequent to said repeating, that said plurality of coefficients of said objective function is said first set of objective function coefficient values; and storing, by said computing system and subsequent to said repeating, said first set of objective function coefficient values in a data storage device of said computing environment.