Despite its great applicability in several industries, the combined cutting stock and lot-sizing problem has not been sufficiently studied because of its great complexity. This paper analyses the trade-off that arises when we solve the cutting stock problem by taking into account the production planning for various periods. An optimal solution for the combined problem probably contains non-optimal solutions for the cutting stock and lot-sizing problems considered separately. The goal here is to minimize the trim loss, the storage and setup costs. With a view to this, we formulate a mathematical model of the combined cutting stock and lot-sizing problem and propose a solution method based on an analogy with the network shortest path problem. Some computational results comparing the combined problem solutions with those obtained by the method generally used in industry—first solve the lot-sizing problem and then solve the cutting stock problem—are presented. These results demonstrate that by combining the problems it is possible to obtain benefits of up to 28% profit. Finally, for small instances we analyze the quality of the solutions obtained by the network shortest path approach compared to the optimal solutions obtained by the commercial package AMPL. 2005 Elsevier B.V. All rights reserved.
[1]
Linda Hendry,et al.
A Cutting Stock and Scheduling Problem in the Copper Industry
,
1996
.
[2]
R. Gomory,et al.
Multistage Cutting Stock Problems of Two and More Dimensions
,
1965
.
[3]
André Gascon,et al.
Solving a one-dimensional cutting-stock problem in a small manufacturing firm: a case study
,
1995
.
[4]
Harvey M. Wagner,et al.
Dynamic Version of the Economic Lot Size Model
,
2004,
Manag. Sci..
[5]
Ravindra K. Ahuja,et al.
Network Flows: Theory, Algorithms, and Applications
,
1993
.
[6]
Robert W. Haessler.
Selection and design of heuristic procedures for solving roll trim problems
,
1988
.
[7]
Anders Thorstenson,et al.
A combined cutting-stock and lot-sizing problem
,
2000,
Eur. J. Oper. Res..
[8]
Robert W. Haessler,et al.
Controlling Cutting Pattern Changes in One-Dimensional Trim Problems
,
1975,
Oper. Res..
[9]
M. P. Reinders,et al.
Cutting stock optimization and integral production planning for centralized wood processing
,
1992
.
[10]
James R. Evans.
An efficient implementation of the Wagner-Whitin algorithm for dynamic lot-sizing
,
1985
.