Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

Sustainable development has become one of the leading global issues over the period of time. Currently, implementation of sustainability in supply chain has been continuously in center of attention due to introducing stringent legislations regarding environmental pollution by various governments and increasing stakeholders’ concerns toward social injustice. Unfortunately, literature is still scarce on studies considering all three dimensions (economical, environmental and social) of sustainability for the supply chain. An effective supply chain network design (SCND) is very important to implement sustainability in supply chain. This study proposes an uncertain SCND model that minimizes the total supply chain-oriented cost and determines the opening of plants, warehouses and flow of materials across the supply chain network by considering various carbon emissions and social factors. In this study, a new AHP and fuzzy TOPSIS-based methodology is proposed to transform qualitative social factors into quantitative social index, which is subsequently used in chance-constrained SCND model with an aim at reducing negative social impact. Further, the carbon emission of supply chain is estimated by considering a composite emission that consists of raw material, production, transportation and handling emissions. In the model, a carbon emission cap is imposed on total supply chain to reduce the carbon footprint of supply chain. To solve the proposed model, a code is developed in AMPL software using a nonlinear solver SNOPT. The applicability of the proposed model is illustrated with a numerical example. The sensitivity analysis examines the effects of reducing carbon footprint cap, negative social impacts and varying probability on the total cost of the supply chain. It is observed that a stricter carbon cap over supply chain network leads to opening of more plants across the supply chain. In addition, carbon footprint of supply chain is found to be decreased in certain extent with the reduction in negative social impacts from suppliers. The carbon footprint of the supply chain is found to be reduced with increasing certainty of material supply from the suppliers. The total supply chain cost is observed to be augmented with increasing probability.

[1]  Mark S. Daskin,et al.  Strategic facility location: A review , 1998, Eur. J. Oper. Res..

[2]  Gonzalo Guillén-Gosálbez,et al.  Optimal design and planning of sustainable chemical supply chains under uncertainty , 2009 .

[3]  Francisco Saldanha-da-Gama,et al.  Facility location and supply chain management - A review , 2009, Eur. J. Oper. Res..

[4]  Xiaofan Lai,et al.  A multi-objective optimization for green supply chain network design , 2011, Decis. Support Syst..

[5]  C. Searcy,et al.  A comparative literature analysis of definitions for green and sustainable supply chain management , 2013 .

[6]  Joseph Sarkis,et al.  Green supply chain management: A review and bibliometric analysis , 2015 .

[7]  Amin Chaabane,et al.  Designing supply chains with sustainability considerations , 2011 .

[8]  Manoj Kumar Tiwari,et al.  A carbon market sensitive optimization model for integrated forward–reverse logistics , 2015 .

[9]  Anurika Vaish,et al.  Suppliers’ green performance evaluation using fuzzy extended ELECTRE approach , 2017, Clean Technologies and Environmental Policy.

[10]  Farzad Dehghanian,et al.  Designing sustainable recovery network of end-of-life products using genetic algorithm , 2009 .

[11]  Faisal Ahmed,et al.  Determination of hierarchical relationships among sustainable development goals using interpretive structural modeling , 2018, Environment, Development and Sustainability.

[12]  De-Li Yang,et al.  Using a hybrid multi-criteria decision aid method for information systems outsourcing , 2007, Comput. Oper. Res..

[13]  Mir Saman Pishvaee,et al.  An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain , 2014 .

[14]  Stefan Seuring,et al.  Integrated chain management in Germany – identifying schools of thought based on a literature review , 2007 .

[15]  C. K. Y. Lin,et al.  Stochastic single-source capacitated facility location model with service level requirements , 2009 .

[16]  V. Swaen,et al.  Corporate Social Responsibility Practices in Developing and Transitional Countries: Botswana and Malawi , 2009 .

[17]  Samir Elhedhli,et al.  Green supply chain network design to reduce carbon emissions , 2012 .

[18]  Manoj Kumar Tiwari,et al.  A Hybrid Taguchi-Immune approach to optimize an integrated supply chain design problem with multiple shipping , 2010, Eur. J. Oper. Res..

[19]  F. Chan,et al.  Global supplier development considering risk factors using fuzzy extended AHP-based approach , 2007 .

[20]  Masood A. Badri,et al.  Combining the analytic hierarchy process and goal programming for global facility location-allocation problem , 1999 .

[21]  S. Seuring,et al.  Sustainable supply chain management and inter-organizational resources: a literature review , 2009 .

[22]  Ali H. Diabat,et al.  An integrated supply chain problem with environmental considerations , 2015 .

[23]  Pu Li,et al.  Chance constrained programming approach to process optimization under uncertainty , 2008, Comput. Chem. Eng..

[24]  P. Chang,et al.  Carbon-efficient production, supply chains and logistics , 2015 .

[25]  Pierre Dejax,et al.  Sustainable supply chain network design: An optimization-oriented review☆ , 2015 .

[26]  Mahmoud M. El-Halwagi,et al.  Optimal planning and site selection for distributed multiproduct biorefineries involving economic, environmental and social objectives. , 2014 .

[27]  Subhash C. Sarin,et al.  Chance Constrained Programming Models for Risk-Based Economic and Policy Analysis of Soil Conservation , 1994, Agricultural and Resource Economics Review.

[28]  Alireza Nazemi,et al.  A high performance neural network model for solving chance constrained optimization problems , 2013, Neurocomputing.

[29]  Ioannis Mallidis,et al.  Operations Research for green logistics - An overview of aspects, issues, contributions and challenges , 2011, Eur. J. Oper. Res..

[30]  Isabel Gallego‐Álvarez,et al.  Evolution of sustainability indicator worldwide: A study from the economic perspective based on the X-STATICO method , 2015 .

[31]  Subhas K. Sikdar,et al.  More on aggregating multiple indicators into a single index for sustainability analyses , 2012, Clean Technologies and Environmental Policy.

[32]  C. Hwang Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[33]  R. Hammami,et al.  Design of forward supply chains: Impact of a carbon emissions-sensitive demand , 2016 .

[34]  Brian R. Gordon,et al.  A Multidimensional Conceptualization of Environmental Velocity , 2010 .

[35]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[36]  R. Gray,et al.  Corporate social and environmental reporting , 1995 .

[37]  F. You,et al.  Optimal design of sustainable cellulosic biofuel supply chains: Multiobjective optimization coupled with life cycle assessment and input–output analysis , 2012 .

[38]  Ralf W. Seifert,et al.  Carbon footprint and responsiveness trade-offs in supply chain network design , 2015 .

[39]  S. Sikdar Sustainability and recycle–reuse in process systems , 2007 .

[40]  Rodolfo Lourenzutti,et al.  A generalized TOPSIS method for group decision making with heterogeneous information in a dynamic environment , 2016, Inf. Sci..

[41]  A. Charnes,et al.  Chance-Constrained Programming , 1959 .

[42]  E. Aghezzaf,et al.  Capacity planning and warehouse location in supply chains with uncertain demands , 2005, J. Oper. Res. Soc..

[43]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[44]  Remica Aggarwal,et al.  Chance constraint-based multi-objective stochastic model for supplier selection , 2015 .

[45]  A. Gunasekaran,et al.  Social sustainability in the supply chain: Construct development and measurement validation , 2016 .

[46]  Olivier Klopfenstein,et al.  Solving chance-constrained combinatorial problems to optimality , 2010, Comput. Optim. Appl..

[47]  Michael J. Maloni,et al.  Corporate Social Responsibility in the Supply Chain: An Application in the Food Industry , 2006 .

[48]  Flavio Tonelli,et al.  Performance measurement of sustainable supply chains : A literature review and a research agenda , 2013 .

[49]  Samir K. Srivastava,et al.  Green Supply-Chain Management: A State-of-the-Art Literature Review , 2007 .

[50]  Mark Goh,et al.  Covering problems in facility location: A review , 2012, Comput. Ind. Eng..

[51]  Ans Kolk,et al.  The Effectiveness of Self-regulation:: Corporate Codes of Conduct and Child Labour , 2002 .

[52]  Urmila M. Diwekar,et al.  Tools and Methods for Pollution Prevention , 1999 .

[53]  Serkan Yavuz,et al.  Weapon selection using the AHP and TOPSIS methods under fuzzy environment , 2009, Expert Syst. Appl..

[54]  G. Zsidisin,et al.  Environmental purchasing: a framework for theory development , 2001 .

[55]  V. Mani,et al.  Supplier selection using social sustainability: AHP based approach in India , 2014 .

[56]  Irfan Ertugrul,et al.  Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods , 2009, Expert Syst. Appl..

[57]  Christopher S. Tang,et al.  Research advances in environmentally and socially sustainable operations , 2012, Eur. J. Oper. Res..

[58]  S. Sikdar Sustainable development and sustainability metrics , 2003 .

[59]  Marcus Brandenburg,et al.  Quantitative models for sustainable supply chain management: Developments and directions , 2014, Eur. J. Oper. Res..

[60]  Xiaofei Xu,et al.  A fuzzy AHP based integer linear programming model for the multi‐criteria transshipment problem , 2012 .

[61]  Lei Zhao,et al.  Interactive decision procedure for watershed nutrient load reduction: An integrated chance-constrained programming model with risk-cost tradeoff , 2014, Environ. Model. Softw..

[62]  Chandra Prakash,et al.  Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment , 2015 .

[63]  Ali H. Diabat,et al.  Green supply chains with carbon trading and environmental sourcing: Formulation and life cycle assessment , 2012 .

[64]  Mark S. Daskin,et al.  Carbon Footprint and the Management of Supply Chains: Insights From Simple Models , 2013, IEEE Transactions on Automation Science and Engineering.

[65]  Vladimir Simic,et al.  Interval-parameter chance-constraint programming model for end-of-life vehicles management under rigorous environmental regulations. , 2016, Waste management.

[66]  B. Hillebrand,et al.  Managing Socially-Responsible Buying:: How to Integrate Non-economic Criteria into the Purchasing Process , 2002 .

[67]  A. Ravindran,et al.  A multiobjective chance constrained programming model for supplier selection under uncertainty , 2011 .

[68]  K. Lai,et al.  An Organizational Theoretic Review of Green Supply Chain Management Literature , 2011 .

[69]  S. Rahman,et al.  Indian textile suppliers' sustainability evaluation using the grey approach , 2012 .

[70]  José Moyano-Fuentes,et al.  Lean Management, Supply Chain Management and Sustainability: A Literature Review , 2014 .

[71]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[72]  A. M. Fet,et al.  What is required for greener supplier selection? A literature review and conceptual model development , 2013 .

[73]  Ying-Ming Wang,et al.  Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment , 2006, Expert Syst. Appl..

[74]  Mir Saman Pishvaee,et al.  Robust possibilistic programming for socially responsible supply chain network design: A new approach , 2012, Fuzzy Sets Syst..

[75]  Kai Huang,et al.  Chance Constrained Optimization for Targeted Internet Advertising , 2014, ArXiv.

[76]  Benita M. Beamon,et al.  Green supply chain network design with stochastic demand and carbon price , 2017, Ann. Oper. Res..

[77]  Mir Saman Pishvaee,et al.  Environmental supply chain network design using multi-objective fuzzy mathematical programming , 2012 .

[78]  A. Barbosa‐Póvoa,et al.  Towards supply chain sustainability: economic, environmental and social design and planning , 2015 .

[79]  S. Chopra,et al.  Supply Chain Management: Strategy, Planning & Operation , 2007 .

[80]  Charbel José Chiappetta Jabbour,et al.  Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company , 2014, Eur. J. Oper. Res..

[81]  JueWang,et al.  AN EXTENSION OF TOPSIS FOR FUZZY MCDM BASED ON VAGUE SET THEORY , 2005 .

[82]  Angappa Gunasekaran,et al.  Flexible Sustainable Supply Chain Network Design: Current Trends, Opportunities and Future , 2016 .

[83]  Yildiz Esra Albayrak,et al.  Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem , 2004, J. Intell. Manuf..

[84]  Nasser Salmasi,et al.  Stochastic scheduling with minimizing the number of tardy jobs using chance constrained programming , 2013, Math. Comput. Model..

[85]  Metin Dagdeviren,et al.  Decision making in equipment selection: an integrated approach with AHP and PROMETHEE , 2008, J. Intell. Manuf..

[86]  P. Miranda,et al.  INCORPORATING INVENTORY CONTROL DECISIONS INTO A STRATEGIC DISTRIBUTION NETWORK DESIGN MODEL WITH STOCHASTIC DEMAND , 2004 .

[87]  Zuo-Jun Max Shen,et al.  An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results , 2002, Ann. Oper. Res..

[88]  John Elkington,et al.  Partnerships from cannibals with forks: The triple bottom line of 21st‐century business , 1998 .

[89]  Haldun Süral,et al.  A review of hierarchical facility location models , 2007, Comput. Oper. Res..

[90]  Alison Ashby,et al.  Making connections: a review of supply chain management and sustainability literature , 2012 .

[91]  Cory Searcy,et al.  An analysis of metrics used to measure performance in green and sustainable supply chains , 2015 .

[92]  Kannan Govindan,et al.  Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future , 2015, Eur. J. Oper. Res..

[93]  Reza Zanjirani Farahani,et al.  Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case , 2013, Eur. J. Oper. Res..

[94]  Qiang Liu,et al.  A study on facility location–allocation problem in mixed environment of randomness and fuzziness , 2011, J. Intell. Manuf..

[95]  Surendra S. Yadav,et al.  An integrated approach of Analytic Hierarchy Process and Fuzzy Linear Programming for supplier selection , 2008 .

[96]  Richard W. Eglese,et al.  Combinatorial optimization and Green Logistics , 2007 .

[97]  Ahmad Jafarian,et al.  Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques , 2014, Eur. J. Oper. Res..

[98]  Baohua Wang,et al.  Stochastic vendor selection problem: chance-constrained model and genetic algorithms , 2009, Ann. Oper. Res..

[99]  Olcay Polat,et al.  A model proposal for green supply chain network design based on consumer segmentation , 2016 .

[100]  Seyed Hassan Ghodsypour,et al.  A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming , 1998 .

[101]  Mark Goh,et al.  Production , Manufacturing and Logistics A stochastic model for risk management in global supply chain networks , 2007 .

[102]  Manoj Kumar Tiwari,et al.  Production planning optimization for manufacturing and remanufacturing system in stochastic environment , 2013, J. Intell. Manuf..

[103]  Stefan Seuring,et al.  A review of modeling approaches for sustainable supply chain management , 2013, Decis. Support Syst..

[104]  Mingzhou Jin,et al.  The impact of carbon policies on supply chain design and logistics of a major retailer , 2014 .

[105]  C. Carter,et al.  Sustainable supply chain management: Evolution and future directions , 2011 .

[106]  Suhua Hsieh,et al.  Demand and cost forecast error sensitivity analyses in aggregate production planning by possibilistic linear programming models , 2000, J. Intell. Manuf..

[107]  Chung-Hsing Yeh,et al.  A survey and optimization-based evaluation of development strategies for the air cargo industry , 2007 .

[108]  Hsu-Shih Shih,et al.  A hybrid MCDM model for strategic vendor selection , 2006, Math. Comput. Model..

[109]  Rosnah Mohd Yusuff,et al.  Integrated supply chain planning under uncertainty using an improved stochastic approach , 2011 .

[110]  Bruno Agard,et al.  Environmental constraints in joint product and supply chain design optimization , 2014, Comput. Ind. Eng..

[111]  D. Wood Corporate Social Performance Revisited , 1991 .

[112]  N. C. Hiremath,et al.  Multi objective outbound logistics network design for a manufacturing supply chain , 2013, J. Intell. Manuf..

[113]  Janjaap Semeijn,et al.  Issues and initiatives surrounding rail freight transportation in Europe , 2002 .

[114]  William Ho,et al.  Integrated analytic hierarchy process and its applications - A literature review , 2008, Eur. J. Oper. Res..

[115]  Konstantinos P. Anagnostopoulos,et al.  An AHP model for construction contractor prequalification , 2006, Oper. Res..

[116]  Alessio Ishizaka,et al.  Review of the main developments in the analytic hierarchy process , 2011, Expert Syst. Appl..

[117]  Semih Onüt,et al.  Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. , 2008, Waste management.

[118]  Angappa Gunasekaran,et al.  The design of a responsive sustainable supply chain network under uncertainty , 2015 .