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ENVIRONMENTAL WASTE CRITERION-BASED SUPPLIER SELECTION PROBLEM

Year 2017, Volume: 5 Issue: 5, 311 - 322, 01.07.2017

Abstract

The environmental sustainability of the supply chain depends on the strategies of its supply chain members. The first models focused on factors such as cost, time of arrival, quality, and carbon emissions, but no consideration was given to environmental waste. Recently, efforts to reduce environmental pollution of supply chains have been increasing. In this study, the environmental waste problem is addressed using Entropy and Fuzzy multi-objective linear programming. The factors discussed here are: cost, percentage of returns, chemical waste rate, demand, percentage of delivery delay. This study presents an integrated approach to selecting the appropriate supplier in the supply chain that addresses the environmental waste problem using entropy and fuzzy multi-objective linear programming. Entropy is first applied to analyze the weight of many factors. These weights of multiple factors are used in fuzzy multi-objective linear programming for supplier selection and quota distribution. A real life problem is addressed to demonstrate the effectiveness of the proposed model. According to the result of the model solution, the purchase of the products in the determined quantities from each supplier was the optimal result

References

  • Adamo, J. M. (1980). Fuzzy decision trees. Fuzzy Sets and Systems, 4(3), 207– 219.
  • Amid, A., Ghodsypour, S. H., & O’Brien, C. (2006). Fuzzy multi-objective linear model for supplier selection in a supply chain. International Journal of Production Economics, 104(2), 394–407.
  • Amin, S. H., Razmi, J., & Zhang, G. (2011). Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming. Expert Systems with Applications, 38(1), 334–342.
  • Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2010). A fuzzy multi criteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126(2), 370–378.
  • Bai, C., & Sarkis, J. (2010). Green supplier development: Analytical evaluation using rough set theory. Journal of Cleaner Production, 18(12), 1200– 1210.
  • Bellman, R. E., & Zadeh, L. A. (1970). Decision making in a fuzzy environment. Management Science, 17(4), 141–164.
  • Boender, C. G. E., DeGraan, J. G., & Lootsma, F. A. (1989). Multiple-criteria decision analysis with fuzzy pairwise comparisons. Fuzzy Sets and Systems, 29(2), 133–143.
  • Bozbura, F. T., Beskese, A., & Kahraman, C. (2007). Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications, 32(4), 1110–1112. 8192.
  • Buyukozkan, G., & Cifci, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164–174.
  • Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3),233–247.5–17.
  • Erkan, E. F., Teke, Ç. & Güleryüz, D. (2016). A Fuzzy Expert System for Risk Self
  • Assessment of Chronic Diseases. IOSR Journal of Computer Engineering 18(6), 29-33.
  • Freeman J., Chen T. (2015). Green supplier selection using an AHP-Entropy- TOPSIS framework. Supply Chain Management: An International Journal, Vol. 20 Iss: 3, pp.327 – 340.
  • Gao, Z., & Tang, L. (2003). A multi-objective model for purchasing of bulk raw materials of a large-scale integrated steel plant. International Journal of Production Economics, 83(3), 325–334.
  • Ghodsypour, S. H., & O’Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics, 56–57(1), 199–212.
  • Handfield, R., Walton, S., Sroufe, R.,&Melnyk, S. (2002). Applying enviromental criteria to supplier assessment: A study in the application of the analytical hierarchy process. European Journal of Operational Research, 141(1), 70–87.
  • Hong, G. H., Park, S. C., Jang, D. S., & Rho, H. M. (2005). An effective supplier selection method for constructing a competitive supply-relationship. Expert Systems with Applications, 28(4), 629–639.
  • Hsu, C. W., & Hu, A. H. (2009). Applying hazardous substance management to supplier selection using analytic network process. Journal of Cleaner Production, 17(2), 255–264.
  • Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170.
  • Lu, Y. Y., Wu, C. H., & Kuo, T. C. (2007). Environmental principles applicable to green supplier evaluation by using multi-objective decision analysis. International Journal of Production Research, 45(18–19), 4317–4331.
  • Shaw, K., Shankar, R., Yadav, S., Thakur, L. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Systems with Applications, 39(9), 8182- 8192.
  • Tiwari, R. N., Dharmahr, S., & Rao, J. R. (1987). Fuzzy goal programming-an additive model. Fuzzy Sets and Systems, 24(1), 27–34.
  • Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1(1), 45–55.

ÇEVRESEL ATIK KRİTERİ TEMELLİ TEDARİKÇİ SEÇİM PROBLEMİ

Year 2017, Volume: 5 Issue: 5, 311 - 322, 01.07.2017

Abstract

Tedarik zincirinin çevresel sürdürülebilirliği tedarik zinciri üyelerinin stratejilerine bağlıdır. İlk modeller maliyet, varış zamanı, kalite, karbon emisyonu gibi unsurlar üzerinde durmuştu ancak çevresel atık konusuna gereken önem verilmemişti. Son zamanlarda tedarik zincirlerinin çevresel kirliliği azaltma ile ilgili çalışmalar artmaktadır. Bu makalede Entropi ve Bulanık çok amaçlı doğrusal programlama kullanarak çevresel atık problemine değinilmektedir. Burada ele alınan faktörler şunlardır: maliyet, geri dönüşlerin yüzdesi, kimyasal atık oranı, talep, teslimatın gecikme yüzdesi. Bu çalışma, entropi ve bulanık çok amaçlı doğrusal programlama yöntemini kullanarak çevresel atık sorununu ele alan tedarik zincirinde uygun tedarikçiyi seçmek için entegre bir yaklaşım sunmaktadır. Entropi, bir çok faktörün ağırlığını analiz etmek için önce uygulanır. Birden fazla faktörün bu ağırlıkları tedarikçi seçimi ve kota dağıtımı için bulanık çok amaçlı doğrusal programlamada kullanılır. Önerilen modelin etkililiğini göstermek için bir gerçek hayat problemi ele alınmıştır. Model çözümünün sonucuna göre her bir tedarikçiden belirlenen miktarlarda ürün alımı optimal sonucu vermiştir

References

  • Adamo, J. M. (1980). Fuzzy decision trees. Fuzzy Sets and Systems, 4(3), 207– 219.
  • Amid, A., Ghodsypour, S. H., & O’Brien, C. (2006). Fuzzy multi-objective linear model for supplier selection in a supply chain. International Journal of Production Economics, 104(2), 394–407.
  • Amin, S. H., Razmi, J., & Zhang, G. (2011). Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming. Expert Systems with Applications, 38(1), 334–342.
  • Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2010). A fuzzy multi criteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126(2), 370–378.
  • Bai, C., & Sarkis, J. (2010). Green supplier development: Analytical evaluation using rough set theory. Journal of Cleaner Production, 18(12), 1200– 1210.
  • Bellman, R. E., & Zadeh, L. A. (1970). Decision making in a fuzzy environment. Management Science, 17(4), 141–164.
  • Boender, C. G. E., DeGraan, J. G., & Lootsma, F. A. (1989). Multiple-criteria decision analysis with fuzzy pairwise comparisons. Fuzzy Sets and Systems, 29(2), 133–143.
  • Bozbura, F. T., Beskese, A., & Kahraman, C. (2007). Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications, 32(4), 1110–1112. 8192.
  • Buyukozkan, G., & Cifci, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164–174.
  • Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3),233–247.5–17.
  • Erkan, E. F., Teke, Ç. & Güleryüz, D. (2016). A Fuzzy Expert System for Risk Self
  • Assessment of Chronic Diseases. IOSR Journal of Computer Engineering 18(6), 29-33.
  • Freeman J., Chen T. (2015). Green supplier selection using an AHP-Entropy- TOPSIS framework. Supply Chain Management: An International Journal, Vol. 20 Iss: 3, pp.327 – 340.
  • Gao, Z., & Tang, L. (2003). A multi-objective model for purchasing of bulk raw materials of a large-scale integrated steel plant. International Journal of Production Economics, 83(3), 325–334.
  • Ghodsypour, S. H., & O’Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics, 56–57(1), 199–212.
  • Handfield, R., Walton, S., Sroufe, R.,&Melnyk, S. (2002). Applying enviromental criteria to supplier assessment: A study in the application of the analytical hierarchy process. European Journal of Operational Research, 141(1), 70–87.
  • Hong, G. H., Park, S. C., Jang, D. S., & Rho, H. M. (2005). An effective supplier selection method for constructing a competitive supply-relationship. Expert Systems with Applications, 28(4), 629–639.
  • Hsu, C. W., & Hu, A. H. (2009). Applying hazardous substance management to supplier selection using analytic network process. Journal of Cleaner Production, 17(2), 255–264.
  • Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170.
  • Lu, Y. Y., Wu, C. H., & Kuo, T. C. (2007). Environmental principles applicable to green supplier evaluation by using multi-objective decision analysis. International Journal of Production Research, 45(18–19), 4317–4331.
  • Shaw, K., Shankar, R., Yadav, S., Thakur, L. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Systems with Applications, 39(9), 8182- 8192.
  • Tiwari, R. N., Dharmahr, S., & Rao, J. R. (1987). Fuzzy goal programming-an additive model. Fuzzy Sets and Systems, 24(1), 27–34.
  • Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1(1), 45–55.
There are 23 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Mehmet Akif Yerlikaya

Burak Efe This is me

Ömer Faruk Efe This is me

Publication Date July 1, 2017
Published in Issue Year 2017 Volume: 5 Issue: 5

Cite

APA Yerlikaya, M. A., Efe, B., & Efe, Ö. F. (2017). ÇEVRESEL ATIK KRİTERİ TEMELLİ TEDARİKÇİ SEÇİM PROBLEMİ. The International New Issues in Social Sciences, 5(5), 311-322.

The International New Issues in Social Sciences, is international, Scientific, peer-reviewed Journal.
Tini-SOS journal is to evaluate scientific articles in the field of social sciences, especially based on field studies structured in accordance with scientific criteria, and conducts studies to publish studies that provide appropriate measures.