BibTex RIS Kaynak Göster

Yıl 2008, Cilt: 9 Sayı: 2, - 2, 05.08.2016

Yılmaz Yücel

Öz

The issue of production planning and optimization has received a consistent attention from researchers and practitioners for decades, and a number of methodologies for modeling and optimizing production lines have been reported in the research community. Although this is an important issue, there is room for improvement. The majority of existing methodologies assume that processing times are deterministic. From the practical point of view, however, the processing times behave in a random fashion. This paper revisits the traditional part-machine allocation problem and proposes a stochastic programming model where the processing times are described by random variables.

Anahtar Kelimeler

Allocation Processing time Stochastic programming Chance Constraint Programming Optimization

Kaynakça

  • Sworder, D. (1969) Feedback control of a class of linear system with jump parameters, IEEE Transactions in Automatic Control, 14(1), pp. 9-14.
  • Wonham, W. (1970) Random differential equations in control theory in probabilistic Methods in Applied Mathematics, Barucha-Reid, A (ed), Academic Press, NY, pp. 131-217.
  • Johnson, S.M (1954) Optimal two-and three-stage production schedules with setup times included, Naval Research Logistics Quarterly, 1, pp. 61-67.
  • Makino, T. (1956) On a scheduling problem, Journal of the Operations Research Society of Japan, 8, pp. 32-44.
  • Rishel, R. (1975) Dynamic Programming and minimum principles for systems with jump Markov disturbances, Journal of the Royal Statistical Society, 46, pp. 353-388.
  • Davis, M. (1984) Piecewise deterministic Markov processes: a general class of non-diffusion stochastic models, Journal of the Royal Statistical Society, 46, pp. 353-388.
  • Vermes, D. (1985) Optimal control of piecewise deterministic Markov process. Stochastic, 14, pp. 165-208.
  • Hillier, S.F. and Lieberman, G.J. (1990) Introduction to Operations Research. Times Roman by Waldman Graphics, Inc.
  • Douglas, S.C. and Roger, W.N. (1998) A methodology for formulating, formalizing, validating, and evaluating a real-time process control advisor, IIE Transactions, 30, pp. 235-245.
  • 0. Lawremce, S.R and Morton T.E. (1998) Patriarch: Hierarchical production scheduling in National Bureau of Standards Special Publication, 724, NBS, Gaithersburg, MD, pp, 87-97.
  • 1. Olafsson, S.R and Shi, L. (2000) A method for scheduling in parallel manufacturing systems with flexible resources. IIE Transactions, 32, 135-146.
  • 2. Allahverdi, Ali (1999) Stochastically minimizing total flowtime in flowshops with no waiting space. European Journal of Operational Research, 113, 101-112.
  • 3. Cheng, T.C. and Gouqing W. (1998) Batching and scheduling to minimize the makespan in the twomachine flowshop. IIE Transactions, 30,447-453.
  • 4. Hodgson, T.J., Cormier, D., Weintraub, A.J., and Zozom, Jr. A. (1998) Satisfying due-dates in large job shops. Management Science, 44, 1442-1446.
  • 5. Rishel, R. (1988) Controlled were process: Modeling optimal control, IEEE Transactions on Automatic Control, 36(9), 1100-1102.
  • 6. Denardo, E.V. (1967) Contractions mappings in the theory underlying dynamic programming. SIAM Review, 9, 156-177.
  • 7. Bbouksa, E., Haurie, A., and Van Delft, C. (1991) A turnpike improvement algorithm for piecewise deterministic control. Optimal Control Applications and Methods, 12, 1-18.
  • 8. Danzig, G. (1995) Linear programming under uncertainty. Management Science, 1, 197-206.
  • 9. George, V. and Mohsem E. (2000) The use of flowlines to simplify routing complexity in two-stage flowshops. IIE Transactions, 32, 678-699.
  • 0. Prabhu, V. (2000) Performance of real-time distributed arrival time control in hierarchical manufacturing systems. IIE Transactions, 32, 323-331.
  • 1. Kouvelis, P., Daniel, L. and George, V. (2000) Robust scheduling of a two-machine flow shop with uncertain processing times. IIE Transactions, 32, 421-432.
  • 2. Hillier S.M (2000) characterizing the optimal allocation of storage space in production line systems with variable processing times. IIE Transactions, 32, 1-8.
  • 3. Brige J.R. and Louveauxn, F. (1997) Introduction to Stochastic Programming. Spinger-verlag, New York, pp, 84152.
  • 4. Mital, K.V. (1984) Optimization Theory and Applications, Willey Eastern Limited, New Delhi, pp, 573- 631.
  • 5. Caramanis, E. and Haurie, A. (1990) Manufacturing flow control and preventive maintenance: a stochastic control approach. IEEE Transactions of Automatic Control, 35(9), 1024-1031.
  • 6. Corroll, D.C. (1956) Heuristic sequencing of single and multiple component jobs. Unpublished Ph.D. thesis, MIT, Cambridge Ma.

ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA

Yıl 2008, Cilt: 9 Sayı: 2, - 2, 05.08.2016

Yılmaz Yücel

Öz

Üretim planlama ve optimizasyonu konusu onlarca yıl boyunca araştırmacılar ve uygulamacıların ilgisini çekmistir ve araştırma camiasında bildirilen çok sayıda modelleme ve üretim optimizasyonu hattı vardır. Bu önemli bir konu olmasına rağmen gelişmelere de açıktır. Var olan metodların çoğu üretim zamanlarının deterministik olduğunu varsayar. Ne var ki uygulamada üretim zamanları tesadüfî şekilde davranır. Bu makale geleneksel parça makina yerleştirme problemini ele alır ve üretim zamanlarının tesadüfi değişken olarak modellendiği bir stokastik programlama modeli önerir.

Anahtar Kelimeler

Stokastik programlama Optimizasyon Şans sınırlandırılmış programlama Proses zamanlarının rassallığı

Kaynakça

  • Sworder, D. (1969) Feedback control of a class of linear system with jump parameters, IEEE Transactions in Automatic Control, 14(1), pp. 9-14.
  • Wonham, W. (1970) Random differential equations in control theory in probabilistic Methods in Applied Mathematics, Barucha-Reid, A (ed), Academic Press, NY, pp. 131-217.
  • Johnson, S.M (1954) Optimal two-and three-stage production schedules with setup times included, Naval Research Logistics Quarterly, 1, pp. 61-67.
  • Makino, T. (1956) On a scheduling problem, Journal of the Operations Research Society of Japan, 8, pp. 32-44.
  • Rishel, R. (1975) Dynamic Programming and minimum principles for systems with jump Markov disturbances, Journal of the Royal Statistical Society, 46, pp. 353-388.
  • Davis, M. (1984) Piecewise deterministic Markov processes: a general class of non-diffusion stochastic models, Journal of the Royal Statistical Society, 46, pp. 353-388.
  • Vermes, D. (1985) Optimal control of piecewise deterministic Markov process. Stochastic, 14, pp. 165-208.
  • Hillier, S.F. and Lieberman, G.J. (1990) Introduction to Operations Research. Times Roman by Waldman Graphics, Inc.
  • Douglas, S.C. and Roger, W.N. (1998) A methodology for formulating, formalizing, validating, and evaluating a real-time process control advisor, IIE Transactions, 30, pp. 235-245.
  • 0. Lawremce, S.R and Morton T.E. (1998) Patriarch: Hierarchical production scheduling in National Bureau of Standards Special Publication, 724, NBS, Gaithersburg, MD, pp, 87-97.
  • 1. Olafsson, S.R and Shi, L. (2000) A method for scheduling in parallel manufacturing systems with flexible resources. IIE Transactions, 32, 135-146.
  • 2. Allahverdi, Ali (1999) Stochastically minimizing total flowtime in flowshops with no waiting space. European Journal of Operational Research, 113, 101-112.
  • 3. Cheng, T.C. and Gouqing W. (1998) Batching and scheduling to minimize the makespan in the twomachine flowshop. IIE Transactions, 30,447-453.
  • 4. Hodgson, T.J., Cormier, D., Weintraub, A.J., and Zozom, Jr. A. (1998) Satisfying due-dates in large job shops. Management Science, 44, 1442-1446.
  • 5. Rishel, R. (1988) Controlled were process: Modeling optimal control, IEEE Transactions on Automatic Control, 36(9), 1100-1102.
  • 6. Denardo, E.V. (1967) Contractions mappings in the theory underlying dynamic programming. SIAM Review, 9, 156-177.
  • 7. Bbouksa, E., Haurie, A., and Van Delft, C. (1991) A turnpike improvement algorithm for piecewise deterministic control. Optimal Control Applications and Methods, 12, 1-18.
  • 8. Danzig, G. (1995) Linear programming under uncertainty. Management Science, 1, 197-206.
  • 9. George, V. and Mohsem E. (2000) The use of flowlines to simplify routing complexity in two-stage flowshops. IIE Transactions, 32, 678-699.
  • 0. Prabhu, V. (2000) Performance of real-time distributed arrival time control in hierarchical manufacturing systems. IIE Transactions, 32, 323-331.
  • 1. Kouvelis, P., Daniel, L. and George, V. (2000) Robust scheduling of a two-machine flow shop with uncertain processing times. IIE Transactions, 32, 421-432.
  • 2. Hillier S.M (2000) characterizing the optimal allocation of storage space in production line systems with variable processing times. IIE Transactions, 32, 1-8.
  • 3. Brige J.R. and Louveauxn, F. (1997) Introduction to Stochastic Programming. Spinger-verlag, New York, pp, 84152.
  • 4. Mital, K.V. (1984) Optimization Theory and Applications, Willey Eastern Limited, New Delhi, pp, 573- 631.
  • 5. Caramanis, E. and Haurie, A. (1990) Manufacturing flow control and preventive maintenance: a stochastic control approach. IEEE Transactions of Automatic Control, 35(9), 1024-1031.
  • 6. Corroll, D.C. (1956) Heuristic sequencing of single and multiple component jobs. Unpublished Ph.D. thesis, MIT, Cambridge Ma.
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA55VV43BN
Bölüm Makaleler
Yazarlar

Yılmaz Yücel Bu kişi benim

Yayımlanma Tarihi 5 Ağustos 2016
Yayımlandığı Sayı Yıl 2008 Cilt: 9 Sayı: 2

Kaynak Göster

APA Yücel, Y. (2016). ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA. Trakya Üniversitesi Fen Bilimleri Dergisi, 9(2), 2.
AMA Yücel Y. ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA. Trakya Univ J Sci. Ağustos 2016;9(2):2.
Chicago Yücel, Yılmaz. “ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA”. Trakya Üniversitesi Fen Bilimleri Dergisi 9, sy. 2 (Ağustos 2016): 2.
EndNote Yücel Y (01 Ağustos 2016) ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA. Trakya Üniversitesi Fen Bilimleri Dergisi 9 2 2.
IEEE Y. Yücel, “ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA”, Trakya Univ J Sci, c. 9, sy. 2, s. 2, 2016.
ISNAD Yücel, Yılmaz. “ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA”. Trakya Üniversitesi Fen Bilimleri Dergisi 9/2 (Ağustos 2016), 2.
JAMA Yücel Y. ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA. Trakya Univ J Sci. 2016;9:2.
MLA Yücel, Yılmaz. “ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA”. Trakya Üniversitesi Fen Bilimleri Dergisi, c. 9, sy. 2, 2016, s. 2.
Vancouver Yücel Y. ÜRETİM PLANLAMASI VE OPTİMİZASYONUNDA KULLANILAN YÖNTEMLERDEN ŞANS SINIRLANDIRILMIŞ PROGRAMLAMA. Trakya Univ J Sci. 2016;9(2):2.