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Aralık Tip-2 Bulanık AHP Yöntemi ile Üçüncü Parti Tersine Lojistik (3PTL) Firma Seçimi

Yıl 2017, Cilt: 20 Sayı: 1, 52 - 67, 28.04.2017

Öz

Ömrü bitmiş ve kullanılmış ürünlerin yönetimi küreselleşme, yasal
düzenlemeler ve artan çevresel farkındalık nedeniyle önemli bir lojistik
faaliyeti haline gelmiştir. Tersine lojistik ağındaki akışın yönetimi özel
altyapı ve uzmanlık gerektirdiği için, işletmelerin ağlarındaki hangi firma ile
çalışacağı önemli bir sorundur. Bu nedenle işletmeler Üçüncü Parti Tersine
Lojistik (3PTL) firmalarına (sağlayıcılarına) yönelmişlerdir. 3PTL,
işletmelerin tersine lojistik ağındaki ihtiyaç duydukları hizmetlerin veya
lojistik faaliyetlerinin dış kaynak kullanılarak karşılanmasıdır. Bu çalışmada,
en iyi 3PTL firma seçimi için yedi kriter ve üç alternatif ile aralık tip-2
bulanık Analitik Hiyerarşi Prosesi (AHP) yöntemi kullanılmıştır. Aralık tip-2
bulanık kümeler, çelişkili kriterlerin olduğu bulanık grup karar verme
problemlerinin belirsizliğini yansıtmada tip-1 bulanık saylardan daha uygun,
daha esnek ve daha akıllıdır. Bu nedenle, Çok Kriterli Karar Verme (ÇKKV)
problemlerinin aralık tip-2 bulanık sayılar ile entegre edilmesi karar verme
sürecinde avantajlar sağlayacaktır. Yapılan uygulama çalışması sonucunda,
uygulanan aralık tip-2 bulanık AHP yöntemin 3PTL firma seçiminde
kullanılabileceği ortaya konulmuştur.
Ömrü bitmiş ve kullanılmış ürünlerin yönetimi küreselleşme, yasal
düzenlemeler ve artan çevresel farkındalık nedeniyle önemli bir lojistik
faaliyeti haline gelmiştir. Tersine lojistik ağındaki akışın yönetimi özel
altyapı ve uzmanlık gerektirdiği için, işletmelerin ağlarındaki hangi firma ile
çalışacağı önemli bir sorundur. Bu nedenle işletmeler Üçüncü Parti Tersine
Lojistik (3PTL) firmalarına (sağlayıcılarına) yönelmişlerdir. 3PTL,
işletmelerin tersine lojistik ağındaki ihtiyaç duydukları hizmetlerin veya
lojistik faaliyetlerinin dış kaynak kullanılarak karşılanmasıdır. Bu çalışmada,
en iyi 3PTL firma seçimi için yedi kriter ve üç alternatif ile aralık tip-2
bulanık Analitik Hiyerarşi Prosesi (AHP) yöntemi kullanılmıştır. Aralık tip-2
bulanık kümeler, çelişkili kriterlerin olduğu bulanık grup karar verme
problemlerinin belirsizliğini yansıtmada tip-1 bulanık saylardan daha uygun,
daha esnek ve daha akıllıdır. Bu nedenle, Çok Kriterli Karar Verme (ÇKKV)
problemlerinin aralık tip-2 bulanık sayılar ile entegre edilmesi karar verme
sürecinde avantajlar sağlayacaktır. Yapılan uygulama çalışması sonucunda,
uygulanan aralık tip-2 bulanık AHP yöntemin 3PTL firma seçiminde
kullanılabileceği ortaya konulmuştur.

Kaynakça

  • Buckley, J. J. (1985), Fuzzy hierarchical analysis, Fuzzy Sets and Systems, 17(3), 233-247.
  • Celik, Erkan; Gumus, Alev Taskin ve Alegoz, Mehmet (2014), A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management, Journal of Intelligent and Fuzzy Systems, 27(6), 2847-2855.
  • Chang, Da-Yong (1996), Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research, 95(3), 649-655.
  • Chen, Shyi-Ming ve Lee, Li-Wei (2010), Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications, 37(4), 2790-2798.
  • Chen, Shyi-Ming ve Lee, Li-Wei (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(1), 824-833.
  • Efendigil, Tuğba; Önüt, Semih ve Kongar, Elif (2008), A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness, Computers & Industrial Engineering, 54(2), 269-287.
  • Erturgut, Ramazan (2016), Lojistik ve Tedarik Zinciri Yönetimi (1. Baskı), Ankara, Nobel Yayın.
  • Govindan, Kannan ve Murugesan, P. (2011), Selection of third‐party reverse logistics provider using fuzzy extent analysis, Benchmarking: An International Journal, 18(1), 149-167.
  • Govindan, Kannan; Palaniappan, Murugesan; Zhu, Qinghua ve Kannan, Devika (2012), Analysis of third party reverse logistics provider using interpretive structural modeling, International Journal of Production Economics, 140(1), 204-211.
  • Göl, Hakan ve Çatay, Bülent (2007), Third‐party logistics provider selection: insights from a Turkish automotive company, Supply Chain Management: An International Journal, 12(6), 379-384.
  • Jayant, A.; Gupta, P.; Garg, S. K. ve Khan, M. (2014), TOPSIS-AHP based approach for selection of reverse logistics service provider: A case study of mobile phone industry, Procedia Engineering, 97, 2147-2156.
  • Kafa, Nadine; Hani, Yasmina ve El Mhamedi, Abederrahman (2014), A Fuzzy Multi Criteria Approach for Evaluating Sustainability Performance of Third - Party Reverse Logistics Providers, IFIP Advances in Information and Communication Technology, 439, 270-277.
  • Kahraman, Cengiz; Öztayşi, Başar; Uçal Sarı, İrem ve Turanoğlu, Ebru (2014), Fuzzy analytic hierarchy process with interval type-2 fuzzy sets, Knowledge-Based Systems, 59, 48-57.
  • Kannan, Govindan; Pokharel, Shaligram ve Kumar, P. Sasi (2009), A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and Recycling, 54(1), 28-36.
  • Kiliç, Mesut ve Kaya, İhsan (2016), The prioritisation of provinces for public grants allocation by a decision-making methodology based on type-2 fuzzy sets, Urban Studies, 53(4), 755-774.
  • Liu, Hao-Tien ve Wang, Wei-Kai (2009), An integrated fuzzy approach for provider evaluation and selection in third-party logistics, Expert Systems with Applications, 36(3, Part 1), 4387-4398.
  • Mendel, Jerry M. (2007), Advances in type-2 fuzzy sets and systems, Information Sciences, 177(1), 84-110.
  • Mendel, Jerry M. (2007), Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint], IEEE Computational Intelligence Magazine, 2(2), 20-29.
  • Mendel, Jerry M.; John, Robert I. ve Liu, Feilong (2006), Interval Type-2 Fuzzy Logic Systems Made Simple, IEEE Transactions on Fuzzy Systems, 14(6), 808-821.
  • Momeni, Ehsan; Azadi, Majid ve Saen, Reza Farzipoor (2015), Measuring the efficiency of third party reverse logistics provider in supply chain by multi objective additive network DEA model, International Journal of Shipping and Transport Logistics, 7(1), 21-41.
  • Karnik, Nilesh N. ve Mendel, Jerry M. (2001), Operations on type-2 fuzzy sets, Fuzzy Sets and Systems, 122(2), 327-348.
  • Oztaysi, Başar (2015), A Group Decision Making Approach Using Interval Type-2 Fuzzy AHP for Enterprise Information Systems Project Selection, J. of Mult.-Valued Logic & Soft Computing, 24, 475–500.
  • Özbek, Aşır ve Eren, Tamer (2013), Analitik Ağ Süreci Yaklaşımıyla Üçüncü Parti Lojistik (3PL) Firma Seçimi, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(1), 95-113.
  • Özkan, Betül; Kaya, İhsan; Cebeci, Ufuk ve Başlıgil, Hüseyin (2015), A Hybrid Multicriteria Decision Making Methodology Based on Type-2 Fuzzy Sets For Selection Among Energy Storage Alternatives International Journal of Computational Intelligence Systems, 8(5), 914-927.
  • Sasikumar, P. ve Haq, A. Noorul (2011), Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling, International Journal of Production Research, 49(11), 3363-3385.
  • Senthil, S., Srirangacharyulu, B. ve Ramesh, A. (2014), A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics, Expert Systems with Applications, 41(1), 50-58.
  • Tavana, Madjid; Zareinejad, Mohsen; Di Caprio, Debora ve Kaviani, Mohamad Amin (2016), An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics, Applied Soft Computing Journal, 40, 544-557.
  • Van Laarhoven, P. J. M. ve Pedrycz, W. (1983), A fuzzy extension of Saaty's priority theory, Fuzzy Sets and Systems, 11(1), 229-241.
  • Zadeh, L. A. (1975), The concept of a linguistic variable and its application to approximate reasoning-I, Information Sciences, 8(3), 199-249.
  • Zarandi, Mohammad Hossein Fazel; Sisakht, Ali Haddad ve Davari, Soheil (2011), Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming, The International Journal of Advanced Manufacturing Technology, 56(5), 809-821.

Third-Party Reverse Logistics (3PTL) Company Selection with Interval Type-2 Fuzzy AHP

Yıl 2017, Cilt: 20 Sayı: 1, 52 - 67, 28.04.2017

Öz

Management of end-of-life and used products has become an important logistics activity due to globalization, government regulations and increasing environmental awareness. Due to the management of return flow usually requires a specific infrastructure and special information, there is an important question which the company will operate in the network. Therefore, companies have turned Third Party Reverse Logistics Providers (3PTLs). 3PTL is a methodology which the services or logistics activities are met from using external sources. In this study, an interval type-2 fuzzy AHP method is used for selection of 3PTL company with seven criteria and three alternatives. Interval type-2 fuzzy sets are more convenient, flexible and intelligent with respect to type-1 fuzzy sets in fuzzy group decision making problems which contains various and conflicting criteria. Thus, integration of interval type-2 fuzzy sets and multi criteria decision making methods will gain benefits in decision making process. The results of numerical example show that interval type-2 fuzzy AHP method can be used in 3PTL company selection.

Kaynakça

  • Buckley, J. J. (1985), Fuzzy hierarchical analysis, Fuzzy Sets and Systems, 17(3), 233-247.
  • Celik, Erkan; Gumus, Alev Taskin ve Alegoz, Mehmet (2014), A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management, Journal of Intelligent and Fuzzy Systems, 27(6), 2847-2855.
  • Chang, Da-Yong (1996), Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research, 95(3), 649-655.
  • Chen, Shyi-Ming ve Lee, Li-Wei (2010), Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications, 37(4), 2790-2798.
  • Chen, Shyi-Ming ve Lee, Li-Wei (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(1), 824-833.
  • Efendigil, Tuğba; Önüt, Semih ve Kongar, Elif (2008), A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness, Computers & Industrial Engineering, 54(2), 269-287.
  • Erturgut, Ramazan (2016), Lojistik ve Tedarik Zinciri Yönetimi (1. Baskı), Ankara, Nobel Yayın.
  • Govindan, Kannan ve Murugesan, P. (2011), Selection of third‐party reverse logistics provider using fuzzy extent analysis, Benchmarking: An International Journal, 18(1), 149-167.
  • Govindan, Kannan; Palaniappan, Murugesan; Zhu, Qinghua ve Kannan, Devika (2012), Analysis of third party reverse logistics provider using interpretive structural modeling, International Journal of Production Economics, 140(1), 204-211.
  • Göl, Hakan ve Çatay, Bülent (2007), Third‐party logistics provider selection: insights from a Turkish automotive company, Supply Chain Management: An International Journal, 12(6), 379-384.
  • Jayant, A.; Gupta, P.; Garg, S. K. ve Khan, M. (2014), TOPSIS-AHP based approach for selection of reverse logistics service provider: A case study of mobile phone industry, Procedia Engineering, 97, 2147-2156.
  • Kafa, Nadine; Hani, Yasmina ve El Mhamedi, Abederrahman (2014), A Fuzzy Multi Criteria Approach for Evaluating Sustainability Performance of Third - Party Reverse Logistics Providers, IFIP Advances in Information and Communication Technology, 439, 270-277.
  • Kahraman, Cengiz; Öztayşi, Başar; Uçal Sarı, İrem ve Turanoğlu, Ebru (2014), Fuzzy analytic hierarchy process with interval type-2 fuzzy sets, Knowledge-Based Systems, 59, 48-57.
  • Kannan, Govindan; Pokharel, Shaligram ve Kumar, P. Sasi (2009), A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and Recycling, 54(1), 28-36.
  • Kiliç, Mesut ve Kaya, İhsan (2016), The prioritisation of provinces for public grants allocation by a decision-making methodology based on type-2 fuzzy sets, Urban Studies, 53(4), 755-774.
  • Liu, Hao-Tien ve Wang, Wei-Kai (2009), An integrated fuzzy approach for provider evaluation and selection in third-party logistics, Expert Systems with Applications, 36(3, Part 1), 4387-4398.
  • Mendel, Jerry M. (2007), Advances in type-2 fuzzy sets and systems, Information Sciences, 177(1), 84-110.
  • Mendel, Jerry M. (2007), Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint], IEEE Computational Intelligence Magazine, 2(2), 20-29.
  • Mendel, Jerry M.; John, Robert I. ve Liu, Feilong (2006), Interval Type-2 Fuzzy Logic Systems Made Simple, IEEE Transactions on Fuzzy Systems, 14(6), 808-821.
  • Momeni, Ehsan; Azadi, Majid ve Saen, Reza Farzipoor (2015), Measuring the efficiency of third party reverse logistics provider in supply chain by multi objective additive network DEA model, International Journal of Shipping and Transport Logistics, 7(1), 21-41.
  • Karnik, Nilesh N. ve Mendel, Jerry M. (2001), Operations on type-2 fuzzy sets, Fuzzy Sets and Systems, 122(2), 327-348.
  • Oztaysi, Başar (2015), A Group Decision Making Approach Using Interval Type-2 Fuzzy AHP for Enterprise Information Systems Project Selection, J. of Mult.-Valued Logic & Soft Computing, 24, 475–500.
  • Özbek, Aşır ve Eren, Tamer (2013), Analitik Ağ Süreci Yaklaşımıyla Üçüncü Parti Lojistik (3PL) Firma Seçimi, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(1), 95-113.
  • Özkan, Betül; Kaya, İhsan; Cebeci, Ufuk ve Başlıgil, Hüseyin (2015), A Hybrid Multicriteria Decision Making Methodology Based on Type-2 Fuzzy Sets For Selection Among Energy Storage Alternatives International Journal of Computational Intelligence Systems, 8(5), 914-927.
  • Sasikumar, P. ve Haq, A. Noorul (2011), Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling, International Journal of Production Research, 49(11), 3363-3385.
  • Senthil, S., Srirangacharyulu, B. ve Ramesh, A. (2014), A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics, Expert Systems with Applications, 41(1), 50-58.
  • Tavana, Madjid; Zareinejad, Mohsen; Di Caprio, Debora ve Kaviani, Mohamad Amin (2016), An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics, Applied Soft Computing Journal, 40, 544-557.
  • Van Laarhoven, P. J. M. ve Pedrycz, W. (1983), A fuzzy extension of Saaty's priority theory, Fuzzy Sets and Systems, 11(1), 229-241.
  • Zadeh, L. A. (1975), The concept of a linguistic variable and its application to approximate reasoning-I, Information Sciences, 8(3), 199-249.
  • Zarandi, Mohammad Hossein Fazel; Sisakht, Ali Haddad ve Davari, Soheil (2011), Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming, The International Journal of Advanced Manufacturing Technology, 56(5), 809-821.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Bölüm Araştırma Makalesi
Yazarlar

Ahmet Çalık

Turan Paksoy

Yayımlanma Tarihi 28 Nisan 2017
Gönderilme Tarihi 8 Şubat 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 20 Sayı: 1

Kaynak Göster

APA Çalık, A., & Paksoy, T. (2017). Aralık Tip-2 Bulanık AHP Yöntemi ile Üçüncü Parti Tersine Lojistik (3PTL) Firma Seçimi. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 20(1), 52-67.

Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.