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Bulanık Çok-Amaçlı Doğrusal Programlama ve Aralık Tip-2 Bulanık AHP Yöntemi İle Yeşil Tedarikçi Seçimi

Yıl 2018, Sayı: 39, 96 - 109, 01.02.2018

Öz

Yeşil Tedarikçi Seçimi YTS son yıllarda şirketler, araştırmacılar ve müşteriler tarafından, yasal düzenlemeler, artan müşteri bilinci, sivil toplum kuruluşları, kamusal ve sosyal sorumluluklar nedeniyle artan bir ilgiyle karşı karşıyadır. Tedarikçi seçimi tedarik zinciri yönetiminde rol oynayan en önemli faktörlerden biridir. Tedarikçilerin çevresel performansının iyileştirilmesi yeşil tedarik zincirlerinin geliştirilmesi için kritik öneme sahiptir. Tedarikçiler, herhangi bir işletmede üretim için gerekli olan hammaddeleri tedarik ettikleri için yeşil tedarik zinciri yönetimi performansını geliştirmede büyük bir öneme sahiptirler. Bu nedenle her geçen gün daha fazla işletme yeşil satın alma, yeşil paketleme ve tersine lojistik gibi iş performansını ve rekabet gücünü artırmaya yönelik çeşitli yeşil girişimlere yatırım yapmaktadırlar. Bununla birlikte, tedarikçi seçiminde fiyat, kalite, teslimat vb. geleneksel kriterler dikkate alınmakta tedarikçilerin yeşil performanslarını ölçmeye yönelik kriterler göz ardı edilmektedir. Firmaların performanslarını ve rekabet gücünü artırıcı amaçlarına ulaşabilmeleri için karar vericiler, YTS problemlerini çözmek için en iyi yöntemi uygulamalı ve en doğru kriterleri seçmelidirler. Genel olarak, yeşil tedarikçi değerlendirme ve seçim problemleri belirsizlik içermekte ve bulanık küme teorisi, çeşitli kriterlere göre tedarikçilerin değerlendirilmesi için dilsel değişkenleri kullanarak karar vericilerin tercihlerini ve görüşlerini anlamlı sonuçlara dönüştürmeye yardımcı olmaktadır. Bilgi eksikliği, sınırlı sayıda niceliksel bilgi, şirketlerin özel bağlamları ve değişen tedarikçi geçmişleri nedeniyle YTS değerlendirme ve seçim problemleri zorlu bir süreçtir. Bu çalışmada aralık tip-2 Bulanık Analitik Hiyerarşi Prosesi BAHP yöntemi ve Bulanık Çok-Amaçlı Doğrusal Programlama BÇADP modeli kullanılarak yeşil tedarikçilerin performanslarının değerlendirilmesi için entegre bir yöntem önerilmiştir. Aralık tip-2 BAHP yöntemi karar vericilerin görüşlerindeki belirsizliği yansıtmada tip-1 bulanık kümelere göre daha uygundur ve ilk aşamada aralık tip-2 BAHP yöntemi kullanılarak YTS’nde ele alınan kriterlerin ağırlıkları elde edilmiştir. İkinci aşamada ise Maliyet, geç teslimat, salınımı, kirlilik üretimi ve çevre dostu malzeme kullanımı gibi amaçları içeren yeni bir BÇADP modeli önerilmiştir. Daha sonra BAHP yönteminden elde edilen ağırlıklar BÇADP modelinde kullanılarak optimal çözüm elde edilmiş ve tedarikçilerin değerlendirmeleri yapılmıştır. Önerilen yöntemin uygulanabilirliği bir örnek üzerinde gösterilmiştir.

Kaynakça

  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2006). “Fuzzy Multiobjective Linear Model for Supplier Selection in a Supply Chain”, International Journal of Production Economics, 104, 394-407.
  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2009). “A Weighted Additive Fuzzy Multiobjective Model for The Supplier Selection Problem under Price Breaks in a Supply Chain”, International Journal of Production Economics, 121, 323-332.
  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2011). “A Weighted Max–Min Model for Fuzzy Multi-Objective Supplier Selection in a Supply Chain”, International Journal of Production Economics, 131, 139-145.
  • Bhardwaj, B.R. (2016). “Role Of Green Policy On Sustainable Supply Chain Management: A Model for Implementing Corporate Social Responsibility (CSR)”, Benchmarking: An International Journal, 23, 456-468.
  • Buckley, J.J. (1985). “Fuzzy Hierarchical Analysis”, Fuzzy Sets and Systems, 17, 233-247.
  • Büyüközkan, G. (2012). “An Integrated Fuzzy Multi-Criteria Group Decision-Making Approach for Green Supplier Evaluation”, International Journal of Production Research, 50, 2892-2909.
  • Büyüközkan, G., & Çifçi, G. (2012). “A Novel Hybrid MCDM Approach Based on Fuzzy Dematel, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Suppliers”, Expert Systems with Applications, 39, 3000-3011.
  • Chen, S.-M., & Lee, L.-W. (2010). “Fuzzy Multiple Attributes Group Decision-Making Based on The Ranking Values and The Arithmetic Operations of Interval Type-2 Fuzzy Sets”, Expert Systems with Applications, 37, 824-833.
  • Chung, C.-C., Chao, L.-C., & Lou, S.-J. (2016). “The Establishment of A Green Supplier Selection and Guidance Mechanism with The ANP and IPA”, Sustainability, 8, 259.
  • Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). “Green Supply Chain Management: A Review and Bibliometric Analysis”, International Journal of Production Economics, 162, 101-114.
  • Fallahpour, A., Olugu, E.U., Musa, S.N., Khezrimotlagh, D., & Wong, K.Y. (2016). “An Integrated Model for Green Supplier Selection Under Fuzzy Environment: Application of Data Envelopment Analysis and Genetic Programming Approach”, Neural Computing and Applications, 27, 707-725.
  • Feyziog̃lu, O., & Büyüközkan, G. (2010). “Evaluation of Green Suppliers Considering Decision Criteria Dependencies”, in: Ehrgott, M., Naujoks, B., Stewart, J.T., Wallenius, J. (Eds.), Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems: Proceedings of the 19th International Conference on Multiple Criteria Decision Making, Auckland, New Zealand, 7th - 12th January 2008. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 145-154.
  • Govindan, K., & Sivakumar, R. (2016). “Green Supplier Selection and Order Allocation in A Low-Carbon Paper Industry: Integrated Multi-Criteria Heterogeneous Decision-Making and Multi-Objective Linear Programming Approaches”, Annals of Operations Research, 238, 243-276.
  • Hosseini, S., & Khaled, A.A. (2016). “A Hybrid Ensemble and AHP Approach for Resilient Supplier Selection”, Journal of Intelligent Manufacturing, 1-22.
  • Igarashi, M., De Boer, L., & Fet, A.M. (2013). “What is Required for Greener Supplier Selection? A Literature Review and Conceptual Model Development”, Journal of Purchasing and Supply Management, 19, 247-263.
  • Kahraman, C., Öztayşi, B., Uçal Sarı, İ., & Turanoğlu, E. (2014). “Fuzzy Analytic Hierarchy Process with Interval Type-2 Fuzzy Sets”, Knowledge-Based Systems, 59, 48-57.
  • Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., & Diabat, A. (2013). “Integrated Fuzzy Multi Criteria Decision Making Method and Multi-Objective Programming Approach for Supplier Selection and Order Allocation in A Green Supply Chain”, Journal of Cleaner Production, 47, 355-367.
  • Mendel, J.M., John, R.I., & Liu, F. (2006). “Interval Type-2 Fuzzy Logic Systems Made Simple”, IEEE Transactions on Fuzzy Systems, 14, 808-821.
  • My Dung, T.T., Luan, N.M., & Quoc, L.H. (2016). “The Analytic Approach Applications in Green Supplier Selection: A Literature Review”, ARPN Journal of Engineering and Applied Sciences, 11, 6754-6762.
  • Seuring, S., & Müller, M. (2008). “From A Literature Review to A Conceptual Framework for Sustainable Supply Chain Management”, Journal of Cleaner Production, 16, 1699-1710.
  • Shahryari Nia, A., Olfat, L., Esmaeili, A., Rostamzadeh, R., & Antuchevičienė, J. (2016). “Using Fuzzy Choquet Integral Operator for Supplier Selection With Environmental Considerations”, Journal of Business Economics and Management, 17, 503-526.
  • Shaw, K., Shankar, R., Yadav, S.S., & Thakur, L.S. (2012). “Supplier Selection Using Fuzzy AHP and Fuzzy Multi-Objective Linear Programming for Developing Low Carbon Supply Chain”, Expert Systems with Applications, 39, 8182-8192.
  • Srivastava, S.K. (2007). “Green Supply-Chain Management: A State-Of-The-Art Literature Review”, International Journal of Management Reviews, 9, 53-80.
  • Taticchi, P., Tonelli, F., & Pasqualino, R. (2013). “Performance Measurement of Sustainable Supply Chains: A Literature Review and A Research Agenda”, International Journal of Productivity and Performance Management, 62, 782-804.
  • Tiwari, R.N., Dharmar, S., & Rao, J.R. (1987). “Fuzzy Goal Programming - An Additive Model”, Fuzzy Sets and Systems, 24, 27-34.
  • Zadeh, L.A. (1975). “The Concept of A Linguistic Variable and Its Application to Approximate Reasoning—I”, Information Sciences, 8, 199-249.
  • Zhang, X., Xu, Z., & Xing, X. (2016). “Hesitant Fuzzy Programming Technique for Multidimensional Analysis of Hesitant Fuzzy Preferences”, OR Spectrum, 38, 789-817.
  • Zimmer, K., Fröhling, M., & Schultmann, F. (2016). “Sustainable Supplier Management - A Review of Models Supporting Sustainable Supplier Selection, Monitoring and Development”, International Journal of Production Research, 54, 1412-1442.
  • Zimmermann, H.J. (1978). “Fuzzy Programming and Linear Programming with Several Objective Functions”, Fuzzy Sets and Systems, 1, 45-55.

Green Supplier Selection with Fuzzy Multi-Linear Programming and Interval Type-2 Fuzzy AHP Method

Yıl 2018, Sayı: 39, 96 - 109, 01.02.2018

Öz

In recent years Green Supplier Selection GSS has been confronted increasingly attention by companies, researchers and customers in recent years due to legislations, increased customer awareness, non-governmental organizations, public and social responsibilities. Supplier selection is one of the most important factor playing a role in supply chain management. Improving the environmental performance of suppliers is a critical importance for development of green supply chains. Suppliers have a great importance for improving the performance of green supply chain management as they supply the raw materials required for production in any business. As a result, more and more organizations are investing in various green initiatives such as green purchasing, green packaging and reverse logistics to improve business performance and competitiveness. However, in supplier selection traditional criteria such as price, quality, delivery, etc. are taken into consideration and other criteria for measuring the green performance of suppliers are ignored. In order to achieve higher performance and competitiveness objectives, decision makers should apply the best method to solve the GSS problems and choose the most appropriate criteria. In general, the green supplier evaluation and selection problems are uncertain and the fuzzy set theory helps to convert decision makers' preferences and opinions into meaningful results using linguistic variables for the evaluation of suppliers according to various criteria. Due to lack of information, limited quantitative information, companies’ specific contexts, and changing supplier histories, GSS evaluation and selection problems are a challenging process. In this study, an integrated method using interval type-2 Fuzzy Analytical Hierarchy Process FAHP method and Fuzzy Multi-Objective Linear Programming FMODP model is proposed for evaluating the performances of green suppliers. The interval type-2 FAHP method is more suitable than the type-1 fuzzy sets to reflect the uncertainty of decision makers' opinions and in the first stage weights of the criteria are obtained by using the interval type-2 FAHP method for the GSS. In the second stage, a new FMODP model is proposed consists of objectives such as cost, late delivery, emission, pollution production and usage of environmentally friendly material. Then weights obtained from the FAHP method are used in the FMODP model and the optimal solution is obtained for evaluation of suppliers. The applicability of the proposed method is demonstrated on an example

Kaynakça

  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2006). “Fuzzy Multiobjective Linear Model for Supplier Selection in a Supply Chain”, International Journal of Production Economics, 104, 394-407.
  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2009). “A Weighted Additive Fuzzy Multiobjective Model for The Supplier Selection Problem under Price Breaks in a Supply Chain”, International Journal of Production Economics, 121, 323-332.
  • Amid, A., Ghodsypour, S.H., & O’Brien, C. (2011). “A Weighted Max–Min Model for Fuzzy Multi-Objective Supplier Selection in a Supply Chain”, International Journal of Production Economics, 131, 139-145.
  • Bhardwaj, B.R. (2016). “Role Of Green Policy On Sustainable Supply Chain Management: A Model for Implementing Corporate Social Responsibility (CSR)”, Benchmarking: An International Journal, 23, 456-468.
  • Buckley, J.J. (1985). “Fuzzy Hierarchical Analysis”, Fuzzy Sets and Systems, 17, 233-247.
  • Büyüközkan, G. (2012). “An Integrated Fuzzy Multi-Criteria Group Decision-Making Approach for Green Supplier Evaluation”, International Journal of Production Research, 50, 2892-2909.
  • Büyüközkan, G., & Çifçi, G. (2012). “A Novel Hybrid MCDM Approach Based on Fuzzy Dematel, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Suppliers”, Expert Systems with Applications, 39, 3000-3011.
  • Chen, S.-M., & Lee, L.-W. (2010). “Fuzzy Multiple Attributes Group Decision-Making Based on The Ranking Values and The Arithmetic Operations of Interval Type-2 Fuzzy Sets”, Expert Systems with Applications, 37, 824-833.
  • Chung, C.-C., Chao, L.-C., & Lou, S.-J. (2016). “The Establishment of A Green Supplier Selection and Guidance Mechanism with The ANP and IPA”, Sustainability, 8, 259.
  • Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). “Green Supply Chain Management: A Review and Bibliometric Analysis”, International Journal of Production Economics, 162, 101-114.
  • Fallahpour, A., Olugu, E.U., Musa, S.N., Khezrimotlagh, D., & Wong, K.Y. (2016). “An Integrated Model for Green Supplier Selection Under Fuzzy Environment: Application of Data Envelopment Analysis and Genetic Programming Approach”, Neural Computing and Applications, 27, 707-725.
  • Feyziog̃lu, O., & Büyüközkan, G. (2010). “Evaluation of Green Suppliers Considering Decision Criteria Dependencies”, in: Ehrgott, M., Naujoks, B., Stewart, J.T., Wallenius, J. (Eds.), Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems: Proceedings of the 19th International Conference on Multiple Criteria Decision Making, Auckland, New Zealand, 7th - 12th January 2008. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 145-154.
  • Govindan, K., & Sivakumar, R. (2016). “Green Supplier Selection and Order Allocation in A Low-Carbon Paper Industry: Integrated Multi-Criteria Heterogeneous Decision-Making and Multi-Objective Linear Programming Approaches”, Annals of Operations Research, 238, 243-276.
  • Hosseini, S., & Khaled, A.A. (2016). “A Hybrid Ensemble and AHP Approach for Resilient Supplier Selection”, Journal of Intelligent Manufacturing, 1-22.
  • Igarashi, M., De Boer, L., & Fet, A.M. (2013). “What is Required for Greener Supplier Selection? A Literature Review and Conceptual Model Development”, Journal of Purchasing and Supply Management, 19, 247-263.
  • Kahraman, C., Öztayşi, B., Uçal Sarı, İ., & Turanoğlu, E. (2014). “Fuzzy Analytic Hierarchy Process with Interval Type-2 Fuzzy Sets”, Knowledge-Based Systems, 59, 48-57.
  • Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., & Diabat, A. (2013). “Integrated Fuzzy Multi Criteria Decision Making Method and Multi-Objective Programming Approach for Supplier Selection and Order Allocation in A Green Supply Chain”, Journal of Cleaner Production, 47, 355-367.
  • Mendel, J.M., John, R.I., & Liu, F. (2006). “Interval Type-2 Fuzzy Logic Systems Made Simple”, IEEE Transactions on Fuzzy Systems, 14, 808-821.
  • My Dung, T.T., Luan, N.M., & Quoc, L.H. (2016). “The Analytic Approach Applications in Green Supplier Selection: A Literature Review”, ARPN Journal of Engineering and Applied Sciences, 11, 6754-6762.
  • Seuring, S., & Müller, M. (2008). “From A Literature Review to A Conceptual Framework for Sustainable Supply Chain Management”, Journal of Cleaner Production, 16, 1699-1710.
  • Shahryari Nia, A., Olfat, L., Esmaeili, A., Rostamzadeh, R., & Antuchevičienė, J. (2016). “Using Fuzzy Choquet Integral Operator for Supplier Selection With Environmental Considerations”, Journal of Business Economics and Management, 17, 503-526.
  • Shaw, K., Shankar, R., Yadav, S.S., & Thakur, L.S. (2012). “Supplier Selection Using Fuzzy AHP and Fuzzy Multi-Objective Linear Programming for Developing Low Carbon Supply Chain”, Expert Systems with Applications, 39, 8182-8192.
  • Srivastava, S.K. (2007). “Green Supply-Chain Management: A State-Of-The-Art Literature Review”, International Journal of Management Reviews, 9, 53-80.
  • Taticchi, P., Tonelli, F., & Pasqualino, R. (2013). “Performance Measurement of Sustainable Supply Chains: A Literature Review and A Research Agenda”, International Journal of Productivity and Performance Management, 62, 782-804.
  • Tiwari, R.N., Dharmar, S., & Rao, J.R. (1987). “Fuzzy Goal Programming - An Additive Model”, Fuzzy Sets and Systems, 24, 27-34.
  • Zadeh, L.A. (1975). “The Concept of A Linguistic Variable and Its Application to Approximate Reasoning—I”, Information Sciences, 8, 199-249.
  • Zhang, X., Xu, Z., & Xing, X. (2016). “Hesitant Fuzzy Programming Technique for Multidimensional Analysis of Hesitant Fuzzy Preferences”, OR Spectrum, 38, 789-817.
  • Zimmer, K., Fröhling, M., & Schultmann, F. (2016). “Sustainable Supplier Management - A Review of Models Supporting Sustainable Supplier Selection, Monitoring and Development”, International Journal of Production Research, 54, 1412-1442.
  • Zimmermann, H.J. (1978). “Fuzzy Programming and Linear Programming with Several Objective Functions”, Fuzzy Sets and Systems, 1, 45-55.
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Ahmet Çalık Bu kişi benim

Yayımlanma Tarihi 1 Şubat 2018
Yayımlandığı Sayı Yıl 2018 Sayı: 39

Kaynak Göster

APA Çalık, A. (2018). Bulanık Çok-Amaçlı Doğrusal Programlama ve Aralık Tip-2 Bulanık AHP Yöntemi İle Yeşil Tedarikçi Seçimi. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(39), 96-109.


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