Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Identifying redundancy in multi-dimensional knapsack constraints based on surrogate constraints

Authors
Choi, JiwoongChoi, In-Chan
Issue Date
2-Dec-2014
Publisher
TAYLOR & FRANCIS LTD
Keywords
redundancy; linear program; surrogate constraints; knapsack constraints; feasibility problems; 65K05; 90C08
Citation
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, v.91, no.12, pp.2470 - 2482
Indexed
SCIE
SCOPUS
Journal Title
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
Volume
91
Number
12
Start Page
2470
End Page
2482
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/96538
DOI
10.1080/00207160.2014.885020
ISSN
0020-7160
Abstract
Redundancy identification techniques play an important role in improving the solvability of a linear program. In this paper, we address the redundancy in multi-dimensional knapsack constraints by proposing a new redundancy identification method. The proposed method is based on the constraint intercepts of Paulraj, Chellappan, and Natesan [A heuristic approach for identification of redundant constraints in linear programming models, Int. J. Comput. Math. 83 (2006), pp. 675-683] and surrogate constraints. In it, feasibility problems are constructed in order to determine the redundancy of the constraints, and are solved by a heuristic algorithm, which is developed to check the redundancy fast. The results of computational experiments show that the proposed method may be used in a preprocessing stage in order to reduce the number of knapsack constraints.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher CHOI, In Chan photo

CHOI, In Chan
College of Engineering (School of Industrial and Management Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE