Patent ID: 7610241

Claim:
A method of identifying a best quote from a pool of RFP responses for implementing a business scenario, the method to be performed by a computer system including a relational database and user interfaces, the method comprising the steps of: gathering data from the RFP responses and existing circuitry, including a plurality of supplier identities s, identities of access circuits n, technologies t and discount levels d associated with each said supplier identity s; specifying a total cost function C of the business scenario as C = ∑ n , s , i ⁢ ⁢ x ⁢ ⁢ ( n , s , t ) · ( ∑ d ⁢ ⁢ ( mrc ⁢ ⁢ ( n , s , t , d ) · m + otc ⁢ ⁢ ( n , s , t , d ) ) · y ⁢ ⁢ ( s , d ) + ( 1 - cursp ⁢ ⁢ ( n , s ) ) · ( mig ⁢ ⁢ ( n , s , t ) + incent ⁢ ⁢ ( n ) ) ) + ∑ n ⁢ ⁢ ( 1 - ∑ n , t ⁢ ⁢ opt ⁢ ⁢ ( n , t ) · x ⁢ ⁢ ( n , s , t ) ) · c ⁢ ⁢ ( n ) · m wherein x(n,s,t) is a binary variable indicating whether a bid by supplier s with technology t is the optimal solution for circuit n; mrc(n,s,t,d) is a bid monthly price for circuit n by supplier s using technology t at discount level d over m months; otc(n,s,t,d) is a one time charge for bid pricing for circuit n by supplier s using technology t at discount level d; y(s,d) is a binary variable indicating whether discount level d is offered by supplier s; cursp(n,s) is a binary variable indicating whether a current supplier for circuit n is supplier s; mig(n,s,t) is a one time migration cost incurred for moving a circuit n to supplier s with technology t; incent(n) is a one time customer incentive for circuit n; opt(n,t) is a technology feasibility indicator for technology t on circuit n and c(n) is a current monthly cost of access circuit n; specifying bid constraints as mathematical constraint rules that are functions of the gathered data; linearizing by the computer system the total cost function C by assigning a possible value to the binary variable y(s,d) indicating discount level y for supplier s; minimizing by the computer system the linearized cost function to find a lowest total cost supplier s at the possible value of the binary variable y(s,d), using a linear programming solver subject to the mathematical constraint rules; repeating by the computer system the linearizing and minimizing steps using additional values of the binary variable y(s,d), until the total cost C is minimized; and selecting the best quote based on the minimized total cost C.