Method for estimating stock levels in production-distribution networks with inventory control

• US 6,078,900 A
• Filed: 10/23/1998
• Issued: 06/20/2000
• Est. Priority Date: 10/23/1998
• Status: Expired due to Term

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Ettl, Markus, Lin, Grace Yuh-Jiun
• Primary Examiner(s): Swann, Tod R.
• Assistant Examiner(s): Patel, Jagdish
• Application Number:
  US09/177,766
• Time in Patent Office: 606 Days
• Field of Search: 705/10, 705/22, 705/8, 705/28, 364/468.03, 364/468.09
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 20/203 Inventory monitoring

Abstract

A method resolves the problem of projecting future stock levels for multiple stockholding locations in production-distribution networks, and minimizing the total dollar delinquency within given inventory budgets or within given allowable inventory holding costs. The invention communicates process control parameters and production-distribution network parameters, computes priorities for each product held at retail locations of the distribution network. It allocates available global and local budgets among products, sets starting stock levels for each product, computes and displays stock levels and the distribution network performance measures.

Claims

1. A method for estimating stock levels of products in at least one warehouse and in plurality of retail locations of a production-distribution network with inventory control, the method comprising the steps of:

communicating process control parameters and production-distribution network parameters;

computing priorities for each of said products held at said retail locations of said production-distribution network;

allocating available global and local budgets among said products;

setting starting stock levels for each of said products;

selecting a stock level calculation mode;

computing stock levels of products and performance measures of said production-distribution network according to min G(x) where,

x is a vector of stock levels x=(x₀₁, x₀₂, . . . X_MN.sbsb.M), subject to a first constraint and a second constraint; and

outputting said computed stock levels and performance measures of said production-distribution network to enable optimization of inventories in said production-distribution network.

2. The method of claim 1, wherein said stock levels of products are represented by ##EQU6## where, M is a number of said retail locations in said production-distribution network,

N₀ is a number of products at a warehouse,

N_i is a number of products at a retail location i, for i=1,2, . . . ,M, and

s_ij is a shortage cost per unit for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i,

b_ij (x) is expected number of back orders for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i.

3. The method of claim 2, wherein said first constraint is represented by

x_ij^min ≦

x_ij ≦

x_ij^max for i=0,1 . . . ,M and j=1,2 . . . ,N_i

where X_0j is a stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij is a stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i,

x_0j^min is a minimum stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij^min is a minimum stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i, and

x_0j^max is a maximum stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij^max is maximum stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i.

4. The method of claim 3, further comprising a step of displaying said stock levels of products and performance measures of said production-distribution network.

5. The method of claim 4, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a first mode comprises the steps of:

a. performing steps (a) through (f) until said allocated budget is no longer less than C as presented by said second constraint;

##EQU7## where c_0j (x) is inventory budget allocated to product j at said warehouse, for j=1,2, . . . ,N₀, and c_ij (x) is inventory budget allocated to product j at said retail location i, for i=1,2, . . . ,M and j=1,2, . . . N_i ;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency;

c. iteratively selecting a next product and repeating step (d) until all said products in said warehouse are computed;

d. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

e. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

f. updating said stock levels, priorities and an allocated budget.

6. The method of claim 4, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a second mode comprises the steps of:

a. performing steps (a) through (g) until said allocated budget for said retailers is no longer less than C_r and said allocated budget for said warehouse is no longer less than C₀ as presented by said second constraint;

##EQU8## where, C₀ is a maximum inventory budget for said warehouse, and C_r denotes a maximum inventory budget for said retailers;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency if allocated budget for said retailers is less than C_r ;

c. skipping steps (d) and (e) if said allocated budget for said warehouse is less than C₀ ;

d. iteratively selecting a next product and repeating step (e) until all said products in said warehouse are computed;

e. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

f. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

g. updating said stock levels, priorities and an allocated budget.

7. The method of claim 4, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a third mode comprises the steps of:

a. performing steps (a) through (g) until a maximum inventory budget for a current retailer is no longer less than C_i as presented by said second constraint;

##EQU9## where, C₀ is a maximum inventory budget for said warehouse, and C_i is a maximum inventory budget for said retail location i, i=1,2, . . . ,M;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency if said maximum inventory budget is less than C_i for a current retailer;

c. iteratively selecting a next product and repeating steps (d) and (e) until all said products in said warehouse are computed;

d. skipping step (e) if said allocated budget for said warehouse is less than C₀ ;

e. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

f. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

g. updating said stock levels, priorities and an allocated budget.

8. A computer program device readable by a machine, tangibly embodying a program of instructions executable by a machine to perform method steps for estimating stock levels of products in at least one warehouse and in plurality of retail locations of a production-distribution network with inventory control, the method comprising the steps of:

communicating process control parameters and production-distribution network parameters;

computing priorities for each of said products held at said retail locations of said production-distribution network;

allocating available global and local budgets among said products;

setting starting stock levels for each of said products;

selecting a stock level calculation mode;

computing stock levels of products and performance measures of said production-distribution network according to min G(x) where,

x is a vector of stock levels x=(x₀₁, x₀₂, . . . x_MN.sbsb.M), subject to a first constraint and a second constraint; and

outputting said computed stock levels and performance measures of said production-distribution network to enable optimization of inventories in said production-distribution network.

9. The computer program device readable by a machine as claimed in claim 8, wherein said stock levels of products is represented by ##EQU10## where, M is a number of said retail locations in said production-distribution network,

N₀ is a number of products at a warehouse,

N_i is a number of products at a retail location i, for i=1,2, . . . ,M, and

s_ij is a shortage cost per unit for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i,

b_ij (x) is expected number of back orders for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i.

10. The computer program device readable by a machine as claimed in claim 9, wherein said first constraint is represented by

x_ij^min ≦

x_ij ≦

x_ij^max for i=0,1 . . . ,M and j=1,2 . . . ,N_i

where x_0j is a stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij is a stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i,

x_0j^min is a minimum stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij^min is a minimum stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i, and

x_0j^max is a maximum stock level for product j at said warehouse j, j=1,2, . . . ,N₀,

x_ij^max is maximum stock level for product j at said retail location i, i=1,2, . . . ,M and j=1,2, . . . ,N_i.

11. The computer program device readable by a machine as claimed in claim 10, further comprising a step of displaying said stock levels of products and performance measures of said production-distribution network.

12. The computer program device readable by a machine as claimed in claim 11, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a first mode comprises the steps of:

a. performing steps (a) through (f) until said allocated budget is no longer less than C as presented by said second constraint;

##EQU11## where c_0j (x) is inventory budget allocated to product j at said warehouse, for j=1,2, . . . ,N₀, and c_ij (x) is inventory budget allocated to product j at said retail location i, for i=1,2, . . . ,M and j=1,2, . . . N_i ;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency;

c. iteratively selecting a next product and repeating step (d) until all said products in said warehouse are computed;

d. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

e. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

f. updating said stock levels, priorities and an allocated budget.

13. The computer program device readable by a machine as claimed in claim 12, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a second mode comprises the steps of:

a. performing steps (a) through (g) until said allocated budget for said retailers is no longer less than C_r and said allocated budget for said warehouse is no longer less than C₀ as presented by said second constraint;

##EQU12## where, C₀ is a maximum inventory budget for said warehouse, and C_r denotes a maximum inventory budget for said retailers;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency if allocated budget for said retailers is less than C_r ;

c. skipping steps (d) and (e) if said allocated budget for said warehouse is less than C₀ ;

d. iteratively selecting a next product and repeating step (e) until all said products in said warehouse are computed;

e. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

f. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

g. updating said stock levels, priorities and an allocated budget.

14. The computer program device readable by a machine as claimed in claim 13, wherein the step of computing stock levels of products and performance measures of said production-distribution network in a third mode comprises the steps of:

a. performing steps (a) through (g) until a maximum inventory budget for a current retailer is no longer less than C_i as presented by said second constraint;

##EQU13## where, C₀ is a maximum inventory budget for said warehouse, and C_i is a maximum inventory budget for said retail location i, i=1,2, . . . ,M;

b. provisionally increasing said stock level of a selected product with a current highest priority at said retail locations and computing a money value delinquency if said maximum inventory budget is less than C_i for a current retailer;

c. iteratively selecting a next product and repeating steps (d) and (e) until all said products in said warehouse are computed;

d. skipping step (e) if said allocated budget for said warehouse is less than C₀ ;

e. provisionally increasing said stock level of a selected product at said warehouse and computing a money value delinquency;

f. permanently increasing said stock level of a selected product that yielded a lowest money value delinquency; and

g. updating said stock levels, priorities and an allocated budget.