A chance constraint based multi-item production planning model using simulation optimization

Name: A chance constraint based multi-item production planning model using simulation optimization
Author: Albey, Erinç, Uzsoy, R., Kempf, K. G.

İsim	A chance constraint based multi-item production planning model using simulation optimization
Yazar	Albey, Erinç, Uzsoy, R., Kempf, K. G.
Basım Tarihi:	2016
Basım Yeri	- IEEE
Konu	Semiconductor industry, Scheduling models, Evolution, Systems
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-5090-4486-3
Kayıt Numarası	9509458d-b7a5-4044-87dc-e07a37dcc4bc
Lokasyon	Industrial Engineering
Tarih	2016
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	We consider a single stage multi-item production-inventory system under stochastic demand. We had previously proposed a production planning model integrating ideas from forecast evolution and inventory theory to plan work releases into a production facility in the face of stochastic demand. However, this model is tractable only if the capacity allocations are exogenous. This paper determines the capacity allocated to each product in each period using a genetic algorithm. Computational experiments reveal that the proposed algorithm outperforms the previous approach in both total cost and service level.
DOI	10.1109/WSC.2016.7822309

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A chance constraint based multi-item production planning model using simulation optimization

Yazar Albey, Erinç, Uzsoy, R., Kempf, K. G.

Basım Tarihi 2016

Basım Yeri - IEEE

Konu Semiconductor industry, Scheduling models, Evolution, Systems

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-5090-4486-3

Kayıt Numarası 9509458d-b7a5-4044-87dc-e07a37dcc4bc

Lokasyon Industrial Engineering

Tarih 2016

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

Örnek Metin We consider a single stage multi-item production-inventory system under stochastic demand. We had previously proposed a production planning model integrating ideas from forecast evolution and inventory theory to plan work releases into a production facility in the face of stochastic demand. However, this model is tractable only if the capacity allocations are exogenous. This paper determines the capacity allocated to each product in each period using a genetic algorithm. Computational experiments reveal that the proposed algorithm outperforms the previous approach in both total cost and service level.

DOI 10.1109/WSC.2016.7822309