A fuzzy multi-objective optimization model for designing a sustainable supply chain forward network: A case study

Document Type: Research Paper


1 Faculty of Accounting, Management and Economic, Yazd University, Yazd, Iran

2 Faculty of Engineering, Industrial Engineering Department, Yazd University, Yazd, Iran


Global warming in the industry sector have forced political leaders to seek sustainable supply chains. The ceramic tile industry (CTI) is a highly competitive industry which has a major impact on the environment. The aim of the current paper is to present a sustainable supply chain in CTI in order to minimize costs, minimize adverse environmental effects as well as increase social benefits. To do so, a multi-period, multi-product, multi-supplier, multi-objective supply chain has been designed. Quality issue with different technologies and capacity limitations for plants, warehouses and distribution centres are considered.
The framework of the proposed supply chain network involves a forward network from suppliers offering different raw materials and ends by delivering produced items to end users. The objectives are minimizing the total cost (e.g. variable and fixed costs), minimizing environmental hazards (e.g. industrial dusts and carbon dioxide emission), and maximizing social benefits (e.g. job opportunities).
The problem is mathematically formulated by a mixed integer non-linear programming model. This model is solved using a fuzzy goal programming approach. Using a numerical experiment, the proposed model is evaluated in CTI sustainable supply chain model. The results are reported fuzzily and provide three values for each decision variable for a period of two months. In addition, a sensitivity analysis is done on some parameters to appraise the validity and feasibility of the model. The results demonstrate that there should be a balance among the three pillars of sustainability in order to reap economic benefits in addition to considering environmental health.   


Main Subjects

Ahi, P. & Searcy, C. (2015). An analysis of metrics used to measure performance in green and sustainable supply chains. Journal of Cleaner Production, 86, 360-377.

Amin, S. H. & Zhang, G. (2012). An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach. Expert Systems with Applications, 39, 6782-6791.

Arkan, F. & Gungor, Z. (2001). An application of fuzzy goal programming to a multiobjective project network problem. Fuzzy sets and systems, 119, 49-58.

Bohner, C. & Minner, S. (2017). Supplier selection under failure risk, quantity and business volume discounts. Computers & Industrial Engineering, 104, 145-155.

Carter, C. R. & Rogers, D. S. (2008). Sustainable supply chain management: toward new theory in logistics management. International Journal of Physical Distribution and Logistics Management, 38, 360-387.

Chaabane, A., Ramudhin, A. & Paquet, M. (2012). Design of sustainable supply chains under the emission trading scheme. International Journal of Production Economics, 135, 37-49.

Charnes, A. & Cooper, W. (1961). Management Models and Industrial Applications of linear programming, J. Wiley.

Chopra, S. & Meindl, P. (2016). Supply chain management: Strategy, planning, and operation.

Daniel, V., Guide, R. & Van Wassenhove, L. N. (2002). Closed-loop supply chains. Quantitative approaches to distribution logistics and supply chain management. Springer.

Emamian, Y., Nakhai, I. & Eydi, A. (2018). Simultaneous reduction of emissions (CO2 and CO) and optimization of production routing problem in a closed-loop supply chain. Journal of Industrial and Systems Engineering, 11, 114-133.

Eskandarpour, M., Dejax, P., Miemczyk, J. & Peton, O. (2015). Sustainable supply chain network design: an optimization-oriented review. Omega, 54, 11-32.

Fahimnia, B., Sarkis, J. & Eshragh, A. (2015). A tradeoff model for green supply chain planning: A leanness-versus-greenness analysis. Omega, 54, 173-190.

Fleischmann, M., Bloemhof-Ruwaard, J. M., Dekker, R., Van Der Laan, E., Van Nunen, J. A. & Van Wassenhove, L. N. (1997). Quantitative models for reverse logistics: A review. European journal of operational research, 103, 1-17.

Gabaldon-Estevan, D., Criado, E. & Monfort, E. (2014). The green factor in European manufacturing: a case study of the Spanish ceramic tile industry. Journal of Cleaner Production, 70, 242-250.

Gabaldon-Estevan, D., Mezquita, A., Ferrer, S. & Monfort, E. (2016). Unwanted effects of European Union environmental policy to promote a post-carbon industry. The case of energy in the European ceramic tile sector. Journal of cleaner production, 117, 41-49.

Ghaithan, A. M., Attia, A. & Duffuaa, S. O. (2017). Multi-objective optimization model for a downstream oil and gas supply chain. Applied Mathematical Modelling, 52, 689-708.

Govindan, K., Soleimani, H. & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240, 603-626.

Guo, Y., Hu, F., Allaoui, H. & Boulaksil, Y. (2019). A distributed approximation approach for solving the sustainable supply chain network design problem. International Journal of Production Research, 57, 3695-3718.

Initiative, G. R. (2013). G4 sustainability reporting guidelines: Implementation manual. GRI: Amsterdam. Downloaded on, 14, 2014.

ISO26000 2010. Guidance on Social Responsibility. International Organization for Standardization.

Kadzinski, M., Tervonen, T., Tomczyk, M. K. & Dekker, R. (2017). Evaluation of multi-objective optimization approaches for solving green supply chain design problems. Omega, 68, 168-184.

Karimi, R., Ghezavati, V. R. & Damghani, K. K. (2015). Optimization of multi-product, multi-period closed loop supply chain under uncertainty in product return rate: case study in Kalleh dairy company. Journal of Industrial and Systems Engineering, 8, 95-114.

Kisomi, M. S., Solimanpur, M. & Doniavi, A. (2016). An integrated supply chain configuration model and procurement management under uncertainty: a set-based robust optimization methodology. Applied Mathematical Modelling, 40, 7928-7947.

Kivimaa, P. & Mickwitz, P. (2011). Public policy as a part of transforming energy systems: framing bioenergy in Finnish energy policy. Journal of Cleaner Production, 19, 1812-1821.

Koroneos, C. & Dompros, A. (2007). Environmental assessment of brick production in Greece. Building and Environment, 42, 2114-2123.

Lai, Y.-J. & Hwang, C.-L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy sets and systems, 49, 121-133.

Li, H., Li, D. & Jiang, D. (2020). Optimising the configuration of food supply chains. International Journal of Production Research, 1-25.

Liu, S. & Papageorgiou, L. G. (2018). Fair profit distribution in multi-echelon supply chains via transfer prices. Omega, 80, 77-94.

Lopez-Gamero, M. D., Molina-Azorin, J. F. & Claver-Cortes, E. (2010). The potential of environmental regulation to change managerial perception, environmental management, competitiveness and financial performance. Journal of Cleaner Production, 18, 963-974.

Masud, A. S. & Hwang, C. (1980). An aggregate production planning model and application of three multiple objective decision methods. International journal of production research, 18, 741-752.

Menezes, R., Neto, H. M., Santana, L., Lira, H., Ferreira, H. & Neves, G. (2008). Optimization of wastes content in ceramic tiles using statistical design of mixture experiments. Journal of the European Ceramic Society, 28, 3027-3039.

Mogale, D., Ghadge, A., Kumar, S. K. & Tiwari, M. K. (2019). Modelling supply chain network for procurement of food grains in India. International Journal of Production Research, 1-20.

Mota, B., Gomes, M. I., Carvalho, A. & Barbosa-Povoa, A. P. (2018). Sustainable supply chains: An integrated modeling approach under uncertainty. Omega, 77, 32-57.

Nutjanni, K. P., Carvalho, M. S. & Costa, L. (2017). Green supply chain design: A mathematical modeling approach based on a multi-objective optimization model. International Journal of Production Economics, 183, 421-432.

Özceylan, E., Demirel, N., Çetinkaya, C. & Demirel, E. (2017). A closed-loop supply chain network design for automotive industry in Turkey. Computers & Industrial Engineering, 113, 727-745.

Rad, R. S. & Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. Journal of Cleaner Production, 196, 1549-1565.

Ramezani, M., Kimiagari, A. M., Karimi, B. & Hejazi, T. H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems, 59, 108-120.

Rebitzer, G., Ekvall, T., Frischknecht, R., Hunkeler, D., Norris, G., Rydberg, T., Schmidt, W.-P., Suh, S., Weidema, B. P. & Pennington, D. W. (2004). Life cycle assessment: Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environment international, 30, 701-720.

Redemann, T. & Specht, E. (2017). Mathematical model to investigate the influence of circulation systems on the firing of ceramics. Energy Procedia, 120, 620-627.

Sabouhi, F. & Jabalameli, M. S. (2019). A stochastic bi-objective multi-product programming model to supply chain network design under disruption risks. Journal of Industrial and Systems Engineering, 12, 196-209.

Shabani, P., Akbarpour Shirazi, M. & Moatarhosseini, S. M. (2018). A comprehensive model for concurrent optimization of product family and its supply chain network design considering reverse logistic. Journal of Industrial and Systems Engineering, 11, 116-131.

Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E. & Shankar, R. (2008). Designing and managing the supply chain: concepts, strategies and case studies, Tata McGraw-Hill Education.

Soleimani, H., Govindan, K., Saghafi, H. & Jafari, H. (2017). Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Computers & Industrial Engineering, 109, 191-203.

Soleimani, H., Seyyed-Esfahani, M. & Shirazi, M. A. (2013). Designing and planning a multi-echelon multi-period multi-product closed-loop supply chain utilizing genetic algorithm. The International Journal of Advanced Manufacturing Technology, 68, 917-931.

Taddeo, R., Simboli, A. & Morgante, A. (2012). Implementing eco-industrial parks in existing clusters. Findings from a historical Italian chemical site. Journal of Cleaner Production, 33, 22-29.

Tang, C. S. & Zhou, S. (2012). Research advances in environmentally and socially sustainable operations. European Journal of Operational Research, 223, 585-594.

Validi, S., Bhattacharya, A. & Byrne, P. J. (2015). A solution method for a two-layer sustainable supply chain distribution model. Computers & Operations Research, 54, 204-217.

Varsei, M. & Polyakovskiy, S. (2017). Sustainable supply chain network design: A case of the wine industry in Australia. Omega, 66, 236-247.

Varsei, M., Soosay, C., Fahimnia, B. & Sarkis, J. (2014). Framing sustainability performance of supply chains with multidimensional indicators. Supply Chain Management: An International Journal, 19, 242-257.

Wang, F., Lai, X. & Shi, N. (2011). A multi-objective optimization for green supply chain network design. Decision Support Systems, 51, 262-269.

Weber, K. M. & Rohracher, H. (2012). Legitimizing research, technology and innovation policies for transformative change: Combining insights from innovation systems and multi-level perspective in a comprehensive ‘failures’ framework. Research Policy, 41, 1037-1047.

Wu, Z. & Pagell, M. (2011). Balancing priorities: Decision-making in sustainable supply chain management. Journal of operations management, 29, 577-590.

Yaghin, R. G. (2018). Integrated multi-site aggregate production-pricing planning in a two-echelon supply chain with multiple demand classes. Applied Mathematical Modelling, 53, 276-295.

Yolmeh, A. & Saif, U. (2020). Closed-loop supply chain network design integrated with assembly and disassembly line balancing under uncertainty: an enhanced decomposition approach. International Journal of Production Research, 1-18.

Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 1, 3-28.

Zailani, S., Jeyaraman, K., Vengadasan, G. & Premkumar, R. (2012). Sustainable supply chain management (SSCM) in Malaysia: A survey. International Journal of Production Economics, 140, 330-340.

Zeng, S., Meng, X., Yin, H., Tam, C. M. & Sun, L. (2010). Impact of cleaner production on business performance. Journal of Cleaner Production, 18, 975-983.