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An exact algorithm for the N-sheet two dimensional single stock-size cutting stock problem.
- Source :
-
Orion . 2015, Vol. 31 Issue 2, p77-94. 18p. 8 Charts. - Publication Year :
- 2015
-
Abstract
- The method introduced in this paper extends the trim-loss problem or also known as 2D rectangular SLOPP to the multiple sheet situation where N same size two-dimensional sheets have to be cut optimally producing demand items that partially or totally satisfy the requirements of a given order. The cutting methodology is constrained to be of the guillotine type and rotation of pieces is allowed. Sets of patterns are generated in a sequential way. For each set found, an integer program is solved to produce a feasible or sometimes optimal solution to the N-sheet problem if possible. If a feasible solution cannot be identified, the waste acceptance tolerance is relaxed somewhat until solutions are obtained. Sets of cutting patterns consisting of N cutting patterns, one for each of the N sheets, is then analysed for optimality using criteria developed here. This process continues until an optimal solution is identified. Finally, it is indicated how a given order of demand items can be totally satisfied in an optimal way by identifying the smallest N and associated cutting patterns to minimize wastage. Empirical results are reported on a set of 120 problem instances based on well known problems from the literature. The results reported for this data set of problems suggest the feasibility of this approach to optimize the cutting stock problem over more than one same size stock sheet. The main contribution of this research shows the details of an extension of the Wang methodology to obtain and prove exact solutions for the multiple same size stock sheet case. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0259191X
- Volume :
- 31
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Orion
- Publication Type :
- Academic Journal
- Accession number :
- 111392356
- Full Text :
- https://doi.org/10.5784/31-2-527