Computer Implemented System for Determining a Distribution Policy for a Single Period Inventory System, Optimization Application Therefor, and Method Therefor, and Decision Support Tool for Facilitating User Determination of a Distribution Policy for a Single Period Inventory System
Computer implemented system for determining a distribution policy for a single period inventory system on the basis of the relative merit of allocating a draw unit of one of a multitude of different consumer items to one of a multitude of different locations in accordance with an allocation decision criterion subject to one or more constraints, an optimization application therefor, and method therefor, and including a Decision Support Tool for facilitating user determination of a distribution policy for a single period inventory system.
1 . A computer implemented Decision Support Tool (DST) for facilitating user determination of a distribution policy for a single period inventory system, wherein:
the DST is operable to receive the mean demands of a consumer item at the locations of the single period inventory system;
the DST is operable to calculate the expected percentages of a parameter associated with the occurrences of sellout at the locations of the single period inventory system for a multitude of expected returns percentages (% ER), or vice versa; and
the DST is operable to output the multitude of expected returns percentages (% ER) against their corresponding expected percentages of the parameter, or vice versa.
2 . The DST according to claim 1 wherein the parameter is the expected number of sellouts of the consumer item at all n locations of the single period inventory system, and the weighted composite allocation decision criterion is given by:
w 1 (% ER(λ,D)−% ER(λ,D 0 ))+w 2 (% ESO(λ,D 0 )−% ESO(λ,D)) where w 1 , and w 2 are weights, and D 0 is an initial draw vector.
3 . The DST according to claim 2 wherein D 0 =λ).
4 . The DST according to claim 1 wherein the parameter is the expected stockout of the consumer item at all n locations of the single period inventory system and the weighted composite allocation decision criterion is given by:
w 1 (% ER(λ,D)−% ER(λ,D 0 ))+w 2 (% EST(−λ,D 0 )−% EST(λ,D)) where w 1 and w 2 are weights, and D 0 is an initial draw vector.
5 . The DST according to claim 4 wherein D 0 =λ.
6 . The DST according to claim 1 wherein the consumer item is a printed media publication.
7 . Computer implemented method for facilitating user determination of a distribution policy for a single period inventory system, the method comprising the steps of:
(a) calculating the corresponding expected percentages of a parameter associated with the occurrences of sellout at the locations of the single period inventory system for a multitude of expected returns percentages (% ER), or vice versa; and
(b) displaying the multitude of expected returns percentages (% ER) against their corresponding expected percentages of the parameter, or vice versa.
8 . The method according to claim 7 wherein the parameter is the expected number of sellouts of the consumer item at all n locations of the single period inventory system, and the weighted composite allocation decision criterion is given by:
w 1 (% ER(λ,D)−% ER(λ,D 0 ))+w 2 (% ESO(λ,D 0 )−% ESO(λ,D)) where w 1 and w 2 are weights, and D 0 is an initial draw vector.
9 . The method according to claim 8 wherein D 0 =λ.
10 . The method according to claim 9 wherein the parameter is the expected stockout of the consumer item at all n locations of the single period inventory system and the weighted composite allocation criterion is given by:
w 1 (% ER(λ,D)−% ER(λ,D 0 ))+w 2 (% EST(λ,D 0 )−% EST(λ,D)) where w 1 and w 2 are weights, and D 0 is an initial draw vector.
11 . The method according to claim 9 wherein D 0 =λ.
12 . The method according to claim 7 wherein the consumer item is a printed media publication.