Abstract
In this study, a software tool which performs the nesting of leather shoe patterns with two-dimensional irregular shapes on natural leather material with irregular shape with minimum wastage has been developed. The software tool is capable of performing both automatic and manual nesting. Automatic nesting process has been performed using the Grey Wolf Optimizer algorithm, which has been popular in the literature in recent years. Manual nesting is designed to be easy to use with the computer mouse. The software was developed with the C# programming language in the Microsoft Visual Studio 2010 environment. As a result, it has been seen that both manual and automatic nesting operations can be accomplished successfully.
Keywords
References
- Gomes, A. M. ve Oliveira, J. F., A 2-exchange heuristic for nesting problems, European Journal of Operational Research, 141(2), 359–370, (2002).
- Gomes, A. M. ve Oliveira, J. F., Solving Irregular Strip Packing problems by hybridising simulated annealing and linear programming, European Journal of Operational Research, 171(3), 811–829, (2006).
- Yuping, Z., Shouwei, J., ve Chunli, Z., A very fast simulated re-annealing algorithm for the leather nesting problem, The International Journal of Advanced Manufacturing Technology, 25(11–12), 1113–1118, (2005).
- Akbulut, D., An edge matching approach for two-dimensional irregular shaped cutting stock problems, Çankaya Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, (2012).
- Elkeran, A., A new approach for sheet nesting problem using guided cuckoo search and pairwise clustering, European Journal of Operational Research, 231(3), 757–769, (2013).
- Timmerman, M., Optimization methods for nesting problems, University West, Department of Engineering Science, Master Thesis, (2013).
- Domović, D., Rolich, T., Grundler, D. ve Bogović, S., Algorithms for 2D nesting problem based on the no-fit polygon, 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics. MIPRO 2014 - Proceeding, 1094–1099, (2014).
- Lee, W. C., Ma, H., ve Cheng, B. W., A heuristic for nesting problems of irregular shapes,” Computer-Aided Design, 40(5), 625–633, (2008).
- Bayır, F., Kesme problemi̇ne sezgi̇sel bi̇r yaklaşım, İstanbul Üniversitesi, Sosyal Bilimleri Enstitüsü, Doktora Tezi, (2012).
- Mirjalili, S. M. ve Lewis, A., Grey Wolf Optimizer, Advances in Engineering Software, 69, 46–61, (2014).
- Song, X., Tang, L., Zhao, S., Zhang, X., Li, L., Huang, J. ve Cai, W., Grey Wolf Optimizer for parameter estimation in surface waves, Soil Dynamics and Earthquake Engineering, 75, 147–157, (2015).
- Mirjalili, S., How effective is the Grey Wolf optimizer in training multi-layer perceptrons, Applied Intelligence, 43(1), 150–161, (2015).
- Tunç, A., Finans Sektörü için Yapay Öğrenme Teknikleri Kullanarak Kredi Kullanabilirliğin Tespiti, Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, (2016).
Abstract
Bu çalışmada iki boyutlu düzensiz şekillere sahip deri ayakkabı kalıplarının, yine düzensiz şekle sahip doğal deri materyali üzerine en az fire verecek şekilde dizilmesini gerçekleştiren bir yazılım geliştirilmiştir. Geliştirilen yazılım hem otomatik dizilim işlemini hem de el ile dizilim işlemini yapabilecek düzeydedir. Otomatik dizilim işlemi, literatürde son yıllarda popüler olan Gri Kurt Optimizasyonu algoritması kullanılarak gerçekleştirilmiştir. El ile dizilim işlemi ise, kullanıcıların bilgisayarın faresini kolaylıkla kullanabilecekleri şekilde tasarlanmıştır. Yazılım, Microsoft Visual Studio 2010 ortamında C# programlama dili ile geliştirilmiştir. Sonuçta hem el ile hem de otomatik olarak dizilim işlemlerinin başarılı bir şekilde yapılabildiği görülmüştür.
References
- Gomes, A. M. ve Oliveira, J. F., A 2-exchange heuristic for nesting problems, European Journal of Operational Research, 141(2), 359–370, (2002).
- Gomes, A. M. ve Oliveira, J. F., Solving Irregular Strip Packing problems by hybridising simulated annealing and linear programming, European Journal of Operational Research, 171(3), 811–829, (2006).
- Yuping, Z., Shouwei, J., ve Chunli, Z., A very fast simulated re-annealing algorithm for the leather nesting problem, The International Journal of Advanced Manufacturing Technology, 25(11–12), 1113–1118, (2005).
- Akbulut, D., An edge matching approach for two-dimensional irregular shaped cutting stock problems, Çankaya Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, (2012).
- Elkeran, A., A new approach for sheet nesting problem using guided cuckoo search and pairwise clustering, European Journal of Operational Research, 231(3), 757–769, (2013).
- Timmerman, M., Optimization methods for nesting problems, University West, Department of Engineering Science, Master Thesis, (2013).
- Domović, D., Rolich, T., Grundler, D. ve Bogović, S., Algorithms for 2D nesting problem based on the no-fit polygon, 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics. MIPRO 2014 - Proceeding, 1094–1099, (2014).
- Lee, W. C., Ma, H., ve Cheng, B. W., A heuristic for nesting problems of irregular shapes,” Computer-Aided Design, 40(5), 625–633, (2008).
- Bayır, F., Kesme problemi̇ne sezgi̇sel bi̇r yaklaşım, İstanbul Üniversitesi, Sosyal Bilimleri Enstitüsü, Doktora Tezi, (2012).
- Mirjalili, S. M. ve Lewis, A., Grey Wolf Optimizer, Advances in Engineering Software, 69, 46–61, (2014).
- Song, X., Tang, L., Zhao, S., Zhang, X., Li, L., Huang, J. ve Cai, W., Grey Wolf Optimizer for parameter estimation in surface waves, Soil Dynamics and Earthquake Engineering, 75, 147–157, (2015).
- Mirjalili, S., How effective is the Grey Wolf optimizer in training multi-layer perceptrons, Applied Intelligence, 43(1), 150–161, (2015).
- Tunç, A., Finans Sektörü için Yapay Öğrenme Teknikleri Kullanarak Kredi Kullanabilirliğin Tespiti, Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, (2016).
Details
| Primary Language | Turkish |
|---|---|
| Journal Section | Research Articles |
| Authors | |
| Publication Date | December 1, 2018 |
| Submission Date | December 8, 2017 |
| Published in Issue | Year 2018 Volume: 20 Issue: 2 |