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Load dependent lead time modelling: a robust optimization approach

Title	Load dependent lead time modelling: a robust optimization approach
Author	Albey, Erinç, Yanıkoğlu, İhsan, Uzsoy, R.
Publication Date:	2018-01-04
Publication Place	- IEEE
Subject	Planning, Optimization, Production planning, Uncertainty, Data models, Throughput
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-153863428-8
Record ID	25875fd1-7a3f-41ec-bf65-30109ef0dc01
Library Location	Industrial Engineering
Date	2018-01-04
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	Although production planning models using nonlinear CFs have shown promising results for semiconductor wafer fabrication facilities, the lack of an effective methodology for estimating the CFs is a significant obstacle to their implementation. Current practice focuses on developing point estimates using least-squares regression approaches. This paper compares the performance of a production planning model using a multi-dimensional CF and its robust counterpart under several experimental settings. As expected, as the level of uncertainty is increased, the resulting production plan deviates from the optimal solution of the deterministic model. On the other hand, production plans found using the robust counterpart are less vulnerable to parameter estimation errors.
DOI	10.1109/WSC.2017.8248067

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Özyeğin University

Load dependent lead time modelling: a robust optimization approach

Author Albey, Erinç, Yanıkoğlu, İhsan, Uzsoy, R.

Publication Date 2018-01-04

Publication Place - IEEE

Subject Planning, Optimization, Production planning, Uncertainty, Data models, Throughput

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-153863428-8

Record ID 25875fd1-7a3f-41ec-bf65-30109ef0dc01

Library Location Industrial Engineering

Date 2018-01-04

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text Although production planning models using nonlinear CFs have shown promising results for semiconductor wafer fabrication facilities, the lack of an effective methodology for estimating the CFs is a significant obstacle to their implementation. Current practice focuses on developing point estimates using least-squares regression approaches. This paper compares the performance of a production planning model using a multi-dimensional CF and its robust counterpart under several experimental settings. As expected, as the level of uncertainty is increased, the resulting production plan deviates from the optimal solution of the deterministic model. On the other hand, production plans found using the robust counterpart are less vulnerable to parameter estimation errors.

DOI 10.1109/WSC.2017.8248067