A new multi-criteria model based on interval type-2 fuzzy sets and EDAS method for supplier evaluation and order allocation with environmental considerations

A new approach is proposed for supplier evaluation and order allocation.Environmental and economic criteria are considered in the proposed approach.Interval type-2 fuzzy sets and the EDAS method are used for supplier evaluation.A multi-objective linear programming is proposed for order allocation.A sensitivity analysis is made to examine effects of environmental criteria on the model. Nowadays environmental performance of suppliers becomes more important because of competitive conditions. Besides, the economic performance has been a significant factor for companies to choose their suppliers. In this paper, a new integrated model is proposed for supplier evaluation and order allocation which considers both environmental and economic factors. We use the EDAS (Evaluation based on Distance from Average Solution) method and interval type-2 fuzzy sets for evaluation of suppliers with respect to environmental criteria. According to this evaluation two parameters are defined for each supplier: positive score and negative score. These parameters, together with cost parameters, are utilized to propose a multi-objective mathematical model for determination of order quantity from each supplier. A numerical example is used in this paper to show the applicability of the proposed integrated model. Also, a sensitivity analysis is made to examine the effect of weighting environmental criteria on total purchasing cost and quantity of order from each supplier. The results show that the proposed model is efficient and applicable for real-world problems.

[1]  Prasenjit Chatterjee,et al.  Integrated QFD-MCDM framework for green supplier selection , 2017 .

[2]  Witold Pedrycz,et al.  An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment , 2017, Eur. J. Oper. Res..

[3]  Ting-Yu Chen,et al.  Multiple criteria decision analysis using prioritised interval type-2 fuzzy aggregation operators and its application to site selection , 2017 .

[4]  Valentinas Podvezko,et al.  MCDM Assessment of a Healthy and Safe Built Environment According to Sustainable Development Principles: A Practical Neighborhood Approach in Vilnius , 2017 .

[5]  Wei Yan,et al.  A Mixed Integer Programming Model for Supplier Selection and Order Allocation Problem with Fuzzy Multiobjective , 2016, Sci. Program..

[6]  Edmundas Kazimieras Zavadskas,et al.  Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection , 2016, Int. J. Comput. Commun. Control.

[7]  Xiaowei Xu,et al.  Multi-criteria decision making approaches for supplier evaluation and selection: A literature review , 2010, Eur. J. Oper. Res..

[8]  R. Sivakumar,et al.  Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches , 2015, Annals of Operations Research.

[9]  Narges Banaeian,et al.  Green Supplier Selection Criteria: From a Literature Review to a Flexible Framework for Determination of Suitable Criteria , 2014 .

[10]  Shamsuddin Ahmed,et al.  Supplier Selection and Quota Allocation Decisions Under Uncertainty: Review and Future Research Directions , 2013 .

[11]  Kannan Govindan,et al.  Multi criteria decision making approaches for green supplier evaluation and selection: a literature review , 2015 .

[12]  Nihal Erginel,et al.  Interval Type-2 Fuzzy Analytic Network Process for Modelling a 311 Third-party Logistics (3PL) Company , 2017, J. Multiple Valued Log. Soft Comput..

[13]  Edmundas Kazimieras Zavadskas,et al.  Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS) , 2015, Informatica.

[14]  Najla Aissaoui,et al.  Supplier selection and order lot sizing modeling: A review , 2007, Comput. Oper. Res..

[15]  H. Zimmermann Fuzzy programming and linear programming with several objective functions , 1978 .

[16]  Dragisa Stanujkic,et al.  An Extension of the EDAS Method Based on the Use of Interval Grey Numbers , 2017 .

[17]  Abdolhamid Safaei Ghadikolaei,et al.  A resilience approach for supplier selection: Using Fuzzy Analytic Network Process and grey VIKOR techniques , 2017 .

[18]  Hamed Mohammadi,et al.  Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty , 2017 .

[19]  Chin-Nung Liao,et al.  Integrated FAHP, ARAS-F and MSGP methods for green supplier evaluation and selection , 2015 .

[20]  Manoranjan Maiti,et al.  A fuzzy multi-criteria group decision making based on ranking interval type-2 fuzzy variables and an application to transportation mode selection problem , 2017, Soft Comput..

[21]  Alev Taskin Gumus,et al.  An outranking approach based on interval type-2 fuzzy sets to evaluate preparedness and response ability of non-governmental humanitarian relief organizations , 2016, Comput. Ind. Eng..

[22]  Ferhan Çebi,et al.  A two-stage fuzzy approach for supplier evaluation and order allocation problem with quantity discounts and lead time , 2016, Inf. Sci..

[23]  Maghsoud Amiri,et al.  Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets , 2014, The International Journal of Advanced Manufacturing Technology.

[24]  İhsan Kaya,et al.  The prioritisation of provinces for public grants allocation by a decision-making methodology based on type-2 fuzzy sets , 2016 .

[25]  Frank Schultmann,et al.  Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development , 2016 .

[26]  Erkan Celik,et al.  A cause and effect relationship model for location of temporary shelters in disaster operations management , 2017 .

[27]  Edmundas Kazimieras Zavadskas,et al.  Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets , 2017 .

[28]  Yang Du,et al.  Demographic Transition and Labour Market Changes: Implications for Economic Development in China , 2014 .

[29]  Jafar Razmi,et al.  Employing fuzzy TOPSIS and SWOT for supplier selection and order allocation problem , 2015 .

[30]  Matt Marx,et al.  Dynamic Commercialization Strategies for Disruptive Technologies: Evidence from the Speech Recognition Industry , 2013, Manag. Sci..

[31]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[32]  Jurgita Antucheviciene,et al.  A New Method of Assessment Based on Fuzzy Ranking and Aggregated Weights (AFRAW) for MCDM Problems Under Type-2 Fuzzy Environment , 2016 .

[33]  Joan Ignasi Moliné,et al.  Order allocation in a multi-supplier environment: review of the literature since 2007 , 2012 .

[34]  Gülsen Akman,et al.  Evaluating suppliers to include green supplier development programs via fuzzy c-means and VIKOR methods , 2015, Comput. Ind. Eng..

[35]  Jerry Mendel,et al.  Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint] , 2007, IEEE Computational Intelligence Magazine.

[36]  M. Setak,et al.  Supplier Selection and Order Allocation Models in Supply Chain Management: A Review , 2012 .

[37]  Fatih Ecer,et al.  Third-party logistics (3Pls) provider selection via Fuzzy AHP and EDAS integrated model , 2017 .

[38]  Eric W.T. Ngai,et al.  Multi-perspective strategic supplier selection in uncertain environments , 2015 .

[39]  Edmundas Kazimieras Zavadskas,et al.  Multiple criteria decision-making techniques in transportation systems: a systematic review of the state of the art literature , 2015 .

[40]  Zhiqiang Wang,et al.  Effects of information technology alignment and information sharing on supply chain operational performance , 2013, Comput. Ind. Eng..

[41]  S. PrasannaVenkatesan,et al.  Multi-objective supplier selection and order allocation under disruption risk , 2016 .

[42]  Amol Singh,et al.  Supplier evaluation and demand allocation among suppliers in a supply chain , 2014 .

[43]  Kamran S. Moghaddam Fuzzy multi-objective model for supplier selection and order allocation in reverse logistics systems under supply and demand uncertainty , 2015, Expert Syst. Appl..

[44]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[45]  Edmundas Kazimieras Zavadskas,et al.  Multi-Criteria Project Selection Using an Extended VIKOR Method with Interval Type-2 Fuzzy Sets , 2015, Int. J. Inf. Technol. Decis. Mak..

[46]  Narges Banaeian,et al.  Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry , 2018, Comput. Oper. Res..

[47]  Felix T. S. Chan,et al.  A fuzzy AHP and fuzzy multi-objective linear programming model for order allocation in a sustainable supply chain: A case study , 2017, Int. J. Comput. Integr. Manuf..

[48]  Prasanta Kumar Dey,et al.  A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments , 2015 .

[49]  İhsan Kaya,et al.  Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey , 2017 .

[50]  Shyi-Ming Chen,et al.  Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets , 2010, Expert Syst. Appl..

[51]  Erkan Celik,et al.  Application of AHP and VIKOR Methods under Interval Type 2 Fuzzy Environment in Maritime Transportation , 2017 .

[52]  Li Zhou,et al.  A novel approach for enhancing green supply chain management using converged interval-valued triangular fuzzy numbers-grey relation analysis , 2018 .

[53]  Abbas Mardani,et al.  Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014 , 2015 .

[54]  Ali Osman Kusakci,et al.  A hybrid type-2 fuzzy based supplier performance evaluation methodology: The Turkish Airlines technic case , 2017, Appl. Soft Comput..

[55]  Prasanta Kumar Dey,et al.  Strategic supplier performance evaluation: a case-based action research of a UK manufacturing organisation , 2015 .

[56]  He-Yau Kang,et al.  A green supplier selection model for high-tech industry , 2009, Expert Syst. Appl..

[57]  Ferhan Çebi,et al.  A multiobjective fuzzy mathematical model for a supply chain problem with the forward and reverse flows , 2016, Int. J. Inf. Decis. Sci..

[58]  Amit Kumar Sinha,et al.  Towards fuzzy preference relationship based on decision making approach to access the performance of suppliers in environmental conscious manufacturing domain , 2017, Comput. Ind. Eng..

[59]  Lin Zhong,et al.  An ELECTRE I-based multi-criteria group decision making method with interval type-2 fuzzy numbers and its application to supplier selection , 2017, Appl. Soft Comput..

[60]  Devika Kannan,et al.  Sustainable supply chain management practices in Indian automotive industry: A multi-stakeholder view , 2018 .

[61]  Liyan Zhang,et al.  An approach for generating design scheme of new market disruptive products driven by function differentiation , 2016, Comput. Ind. Eng..

[62]  Chong Liu,et al.  Algorithms for Neutrosophic Soft Decision Making Based on Edas and New Similarity Measure , 2017 .

[63]  S. Senturk,et al.  Interval Type-2 Fuzzy Analytic Network Process for Modelling a Third-party Logistics ( 3 PL ) Company , 2016 .

[64]  Adil Baykasolu,et al.  Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS , 2017, Expert Syst. Appl..

[65]  Siba Sankar Mahapatra,et al.  Dominance based fuzzy decision support framework for g-resilient (ecosilient) supplier selection: an empirical modelling , 2017 .

[66]  Doreen Richter Demographic change and innovation: The ongoing challenge from the diversity of the labor force , 2014 .

[67]  Xu Ze Algorithm for priority of fuzzy complementary judgement matrix , 2001 .

[68]  Adil Baykasoglu,et al.  Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS , 2017, Expert Syst. Appl..

[69]  Ming-Chuan Chiu,et al.  Technical service platform planning based on a company's competitive advantage and future market trends: A case study of an IC foundry , 2016, Comput. Ind. Eng..

[70]  Sunil Mithas,et al.  How Information Technology Strategy and Investments Influence Firm Performance: Conjecture and Empirical Evidence , 2016, MIS Q..

[71]  Heikki Karjaluoto,et al.  Environmental values and customer-perceived value in industrial supplier relationships , 2017 .

[72]  Alev Taskin Gumus,et al.  A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets , 2015, Knowl. Based Syst..

[73]  Maghsoud Amiri,et al.  A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach , 2016 .

[74]  Edmundas Kazimieras Zavadskas,et al.  Application of multiple-criteria decision-making techniques and approaches to evaluating of service quality: a systematic review of the literature , 2015 .

[75]  R. Klassen,et al.  Drivers and Enablers That Foster Environmental Management Capabilities in Small‐ and Medium‐Sized Suppliers in Supply Chains , 2008 .

[76]  Zenonas Turskis,et al.  A novel hybrid multi-criteria decision-making model to assess a stairs shape for dwelling houses , 2016 .

[77]  Kannan Govindan,et al.  Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain , 2017 .

[78]  Sadeque Hamdan,et al.  Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach , 2017, Comput. Oper. Res..

[79]  Jian-qiang Wang,et al.  An Interval Type-2 Fuzzy Likelihood-Based MABAC Approach and Its Application in Selecting Hotels on a Tourism Website , 2017, Int. J. Fuzzy Syst..

[80]  Morteza Yazdani,et al.  Intuitionistic fuzzy edas method: an application to solid waste disposal site selection , 2017 .

[81]  Reza Rostamzadeh,et al.  Using fuzzy Choquet Integral operator for supplier selection with environmental considerations , 2016 .

[82]  Xindong Peng,et al.  Interval-valued Fuzzy Soft Decision Making Methods Based on MABAC, Similarity Measure and EDAS , 2017, Fundam. Informaticae.

[83]  Frederico G. Guimarães,et al.  A multi-objective model for the green capacitated location-routing problem considering environmental impact , 2017, Comput. Ind. Eng..

[84]  Muhammet Deveci,et al.  Airline new route selection based on interval type-2 fuzzy MCDM: A case study of new route between Turkey- North American region destinations , 2017 .

[85]  Valentinas Podvezko,et al.  Evaluation of quality assurance in contractor contracts by multi-attribute decision-making methods , 2017 .

[86]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[87]  Chandra Prakash Garg,et al.  An integrated framework for sustainable supplier selection and evaluation in supply chains , 2017 .

[88]  Chong Liu,et al.  Algorithms for neutrosophic soft decision making based on EDAS, new similarity measure and level soft set , 2018, J. Intell. Fuzzy Syst..