Araştırma Makalesi
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AMBAR DEPOLAMA MAKSİMİZASYONU

Yıl 2016, Cilt: 27 Sayı: 4, 26 - 38, 19.01.2017

Öz

Bu çalışmada, zaman içinde değişiklik gösteren müşteri talepleri karşısında etkin depolamanın sağlanabilmesi amacıyla mamul ambarında maksimum depolama alanı ve hacmi sağlayacak şekilde, kasa tipleri ve hacimlerine göre ambar içinde ayrılacak alanların hesaplanması amaçlanmıştır. Bu amaçlar doğrultusunda, problemin değişik versiyonlarını çözmek üzere adet matematiksel model geliştirilmiştir. Bu modeller ihtiyaca göre tekil olarak ele alınabileceği gibi, bu çalışmada ardışık şekilde çözülmektedir; bir modelin sonucu ardışık modellerde girdi olarak kullanılmaktadır. Problemin NP-Zor sınıfına dahil olması sonucu, son model çıktılarının kabul edilebilir zamanda elde edilememesinden dolayı sezgisel bir algoritma geliştirilmiştir. Sezgisel algoritmanın firmada faal olarak kullanılabilmesi için kodlama faaliyetleri ile bir araç geliştirilmiştir. Çalışma sonucunda, işçilik maliyetlerinden ve depolama alanında kazanç elde edilerek, yıllık olarak 74.340,79 TL tasarruf hesaplanmıştır.

Kaynakça

  • 1. Beasley, J. E. 1985. “An Exact Two-Dimensional non-Guillotine Cutting Tree Search Procedure,” Operations Research, vol. 33(1), p. 49-64.
  • 2. Bischoff, E. E., Janetz, F., Ratcliff, M. S. W. 1995. Loading Pallets with non-Identical Items,” European journal of Operational Research, vol. 84 (3), p. 681-692.
  • 3. Chen, C. S., Sarin, S., Ram, B. 1991. “The Pallet Packing Problem for non-Uniform Box Sizes,” The Internatıonal Journal of Productıon Research, vol. 29 (10), p. 1963-1968.
  • 4. Chen, C. S., Lee, S. M., Shen, Q. S. 1995. An Analytical Model for the Container Loading Problem,” European Journal of Operational Research, vol. 80 (1), p. 68-76.
  • 5. Christofides, N., Whitlock, C. 1977. “An Algorithm for Two-Dimensional Cutting Problems,” Operations Research, vol. 25 (1), p. 30-44.
  • 6. Dereli, T., Daş, G. S. 2010. “Development of a Decision Support System for Solving Container Loading Problems,” Transport, vol. 25 (2), p. 138-147.
  • 7. Dowsland, K. A. 1987. “A Combined Data-Base and Algorithmic Approach to the Pallet-Loading Problem,” Journal of the Operational Research Society, vol. 38 (4), p. 341-345.
  • 8. Gademann, A. J. R. M., Van Den Berg, J. P., Van Der Hoff, H. H. 2001. “An Order Batching Algorithm for Wave Picking in a Parallel-Aisle Warehouse,” International Transactions in Operational Research, vol. 33 (5), p. 385-398.
  • 9. Gehring, H., Bortfeldt, A. 1997. “A Genetic Algorithm for Solving the Container Loading Problem,” International Transactions in Operational Research, vol. 4 (5-6), p. 401-418.
  • 10. Hodgson, T. J. 1982. “A Combined Approach to the Pallet Loading Problem," International Transactions in Operational Research, vol. 14 (3), p. 175-182.
  • 11. Huang, W., He, K. 2009. “A Caving Degree Approach for the Single Container Loading Problem,” European Journal of Operational Research, vol. 196 (1), p. 93-101.
  • 12. Jain, S., Gea, H. C. 1998. Two-Dimensional Packing Problems Using Genetic Algorithms,” Engineering with Computers, vol. 14 (3), p. 206-213.
  • 13. Kröger, B., Schwenderling, P., Vornberger, O. 1993. Parallel Genetic Packing on Transputers. Parallel Genetic Algorithms: Theory and Applications, J. Stender, IOS Press, Amsterdam, p.151-185.
  • 14. Muppani, V. R., Adil, G. K. 2008. “A Branch and Bound Algorithm for Class Based Storage Location Assignment,” European Journal of Operational Research, vol. 189 (2), p. 492-507.
  • 15. Pisinger, D. 2002. “Heuristics for the Container Loading Problem,” European Journal of Operational Research, vol. 141 (2), p. 382-392.
  • 16. Scheithauer, G., Sommerweiß, U. 1998. “4-Block Heuristic for the Rectangle Packing Problem,” European Journal of Operational Research, vol. 108 (3), p. 509-526.
  • 17. Steudel, H. J. 1979. “Generating Pallet Loading Patterns: A Special Case of the Two-Dimensional Cutting Stock Problem,” Management Science, vol. 25 (10), p. 997-1004.
  • 18. Terno, J., Scheithauer, G., Sommerweiß, U., Riehme, J. 2000. “An Efficient Approach for the Multi-Pallet Loading Problem,” European Journal of Operational Research, vol. 123 (2), 372-381.
  • 19. Vasko, F. J. 1989. “A Computational Improvement to Wang's Two-Dimensional Cutting Stock Algorithm,” Computers & Industrial Engineering, vol. 16 (1), p. 109-115.
  • 20. Wang, P. Y. 1983. “Two Algorithms for Constrained Two-Dimensional Cutting Stock Problems,” Operations Research, vol. 31 (3), p. 573-586.
  • 21. Wisittipanich, W., Meesuk, P. 2015. Particle Swarm Optimization with Multiple Learning Terms for Storage Location Assignment Problems Considering Three-Axis Traveling Distance," In Toward Sustainable Operations of Supply Chain and Logistics Systems, V. Kachitvichynaukul, K.Sethanan, Kanchana, P.Golińska- Dawson (Eds.), Springer International Publishing, Switzerland, p. 435-443.

MAXIMIZATION OF WAREHOUSE STORAGE

Yıl 2016, Cilt: 27 Sayı: 4, 26 - 38, 19.01.2017

Öz

The objective of this study is to ensure effective warehouse storage in face of ever changing customer demands, through providing maximum storage space and volume by calculating the space to be allocated in the warehouse, with respect to box sizes and volumes. In accordance with this purpose, three mathematical models have been developed to solve different versions of the problem. Although these models can be handled individually as required, they are used sequentially in this study; the result of a model is used as an input for subsequent models. A heuristic was developed, since the last problem is of Np-hard nature, and the results could not be attained in feasible time. The heuristic is coded to be used as a tool for daily storage activities. As a result of the study, 74.340,79 TL savings in personnel costs and storage area costs is calculated.

Kaynakça

  • 1. Beasley, J. E. 1985. “An Exact Two-Dimensional non-Guillotine Cutting Tree Search Procedure,” Operations Research, vol. 33(1), p. 49-64.
  • 2. Bischoff, E. E., Janetz, F., Ratcliff, M. S. W. 1995. Loading Pallets with non-Identical Items,” European journal of Operational Research, vol. 84 (3), p. 681-692.
  • 3. Chen, C. S., Sarin, S., Ram, B. 1991. “The Pallet Packing Problem for non-Uniform Box Sizes,” The Internatıonal Journal of Productıon Research, vol. 29 (10), p. 1963-1968.
  • 4. Chen, C. S., Lee, S. M., Shen, Q. S. 1995. An Analytical Model for the Container Loading Problem,” European Journal of Operational Research, vol. 80 (1), p. 68-76.
  • 5. Christofides, N., Whitlock, C. 1977. “An Algorithm for Two-Dimensional Cutting Problems,” Operations Research, vol. 25 (1), p. 30-44.
  • 6. Dereli, T., Daş, G. S. 2010. “Development of a Decision Support System for Solving Container Loading Problems,” Transport, vol. 25 (2), p. 138-147.
  • 7. Dowsland, K. A. 1987. “A Combined Data-Base and Algorithmic Approach to the Pallet-Loading Problem,” Journal of the Operational Research Society, vol. 38 (4), p. 341-345.
  • 8. Gademann, A. J. R. M., Van Den Berg, J. P., Van Der Hoff, H. H. 2001. “An Order Batching Algorithm for Wave Picking in a Parallel-Aisle Warehouse,” International Transactions in Operational Research, vol. 33 (5), p. 385-398.
  • 9. Gehring, H., Bortfeldt, A. 1997. “A Genetic Algorithm for Solving the Container Loading Problem,” International Transactions in Operational Research, vol. 4 (5-6), p. 401-418.
  • 10. Hodgson, T. J. 1982. “A Combined Approach to the Pallet Loading Problem," International Transactions in Operational Research, vol. 14 (3), p. 175-182.
  • 11. Huang, W., He, K. 2009. “A Caving Degree Approach for the Single Container Loading Problem,” European Journal of Operational Research, vol. 196 (1), p. 93-101.
  • 12. Jain, S., Gea, H. C. 1998. Two-Dimensional Packing Problems Using Genetic Algorithms,” Engineering with Computers, vol. 14 (3), p. 206-213.
  • 13. Kröger, B., Schwenderling, P., Vornberger, O. 1993. Parallel Genetic Packing on Transputers. Parallel Genetic Algorithms: Theory and Applications, J. Stender, IOS Press, Amsterdam, p.151-185.
  • 14. Muppani, V. R., Adil, G. K. 2008. “A Branch and Bound Algorithm for Class Based Storage Location Assignment,” European Journal of Operational Research, vol. 189 (2), p. 492-507.
  • 15. Pisinger, D. 2002. “Heuristics for the Container Loading Problem,” European Journal of Operational Research, vol. 141 (2), p. 382-392.
  • 16. Scheithauer, G., Sommerweiß, U. 1998. “4-Block Heuristic for the Rectangle Packing Problem,” European Journal of Operational Research, vol. 108 (3), p. 509-526.
  • 17. Steudel, H. J. 1979. “Generating Pallet Loading Patterns: A Special Case of the Two-Dimensional Cutting Stock Problem,” Management Science, vol. 25 (10), p. 997-1004.
  • 18. Terno, J., Scheithauer, G., Sommerweiß, U., Riehme, J. 2000. “An Efficient Approach for the Multi-Pallet Loading Problem,” European Journal of Operational Research, vol. 123 (2), 372-381.
  • 19. Vasko, F. J. 1989. “A Computational Improvement to Wang's Two-Dimensional Cutting Stock Algorithm,” Computers & Industrial Engineering, vol. 16 (1), p. 109-115.
  • 20. Wang, P. Y. 1983. “Two Algorithms for Constrained Two-Dimensional Cutting Stock Problems,” Operations Research, vol. 31 (3), p. 573-586.
  • 21. Wisittipanich, W., Meesuk, P. 2015. Particle Swarm Optimization with Multiple Learning Terms for Storage Location Assignment Problems Considering Three-Axis Traveling Distance," In Toward Sustainable Operations of Supply Chain and Logistics Systems, V. Kachitvichynaukul, K.Sethanan, Kanchana, P.Golińska- Dawson (Eds.), Springer International Publishing, Switzerland, p. 435-443.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Gizem Gül Bu kişi benim

Begüm Erol

Gözde Öngelen Bu kişi benim

Sedat Eser Bu kişi benim

Çağdaş Çetinkaya Bu kişi benim

Hüseyin Cenk Özmutlu

Seda Özmutlu

Mehmet Gökçedağlıoğlu Bu kişi benim

Cemil Günhan Erhuy Bu kişi benim

Yayımlanma Tarihi 19 Ocak 2017
Kabul Tarihi 21 Aralık 2016
Yayımlandığı Sayı Yıl 2016 Cilt: 27 Sayı: 4

Kaynak Göster

APA Gül, G., Erol, B., Öngelen, G., Eser, S., vd. (2017). AMBAR DEPOLAMA MAKSİMİZASYONU. Endüstri Mühendisliği, 27(4), 26-38.

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