Document Type

Article

Publication Date

2018

DOI

10.1016/j.promfg.2018.10.134

Publication Title

Procedia Manufacturing

Volume

17

Pages

827-834

Conference Name

28th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2018), June 11-14, 2018, Columbus, OH, USA

Abstract

The one-dimensional cutting stock problem describes the problem of cutting standard length stock material into various specified sizes while minimizing the material wasted (the remnant or drop as manufacturing terms). This computationally complex optimization problem has many manufacturing applications. One-dimensional cutting stock problems arise in many domains such as metal, paper, textile, and wood. To solve it, the problem is formulated as an integer linear model first, and then solved using a common optimizer software. This paper revisits the stochastic version of the problem and proposes a priority-based goal programming approach. Monte Carlo simulation is used to simulate several likely inventory order policies to minimize the total number of shortages, overages, and the number of stocks carried in inventory.

Original Publication Citation

Sarper, H., & Jaksic, N. I. (2018). Evaluation of procurement scenarios in one-dimensional cutting stock problem with a random demand mix. Procedia Manufacturing, 17, 827-834. doi:10.1016/j.promfg.2018.10.134

ORCID

0000-0002-8109-0575 (Sarper)

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