Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/78595 
Year of Publication: 
2012
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 8 [Publisher:] Springer [Place:] Heidelberg [Year:] 2012 [Pages:] 1-8
Publisher: 
Springer, Heidelberg
Abstract: 
A cutting stock problem is one of the main and classical problems in operations research that is modeled as LP problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results are compared. The results show that the proposed SA gives good results in terms of objective function values rather than TS.
Subjects: 
one-dimensional cutting stock problem
mathematical model
simulated annealing
tabu search
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size
307.12 kB





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