Abstract
This chapter mainly discusses the mathematical programming models and methods used to design sustainable logistics networks (SLN) under epistemic uncertainty. Firstly, the relevant concepts and definitions are described and analyzed. Thereafter, a systemic review and analysis of the recent literature is provided to explore the most attractive research avenues in this area. A comprehensive description is given on environmental and social impact assessment methods in order to facilitate the quantification of environmental and social burden in the mathematical decision models. Two selected mathematical programming models for SLN design problem under uncertain data are provided and explained in detail to support quantitative decision-making in this area. Finally, a real industrial case study is described and investigated to show the applicability of the previously discussed mathematical programming methods.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Azadeh, A., Raoofi, Z., Zarrin, M.: A multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction approach. J. Nat. Gas Sci. Eng. 26, 702–710 (2015)
Babazadeh, R., Razmi, J., Pishvaee, M.S., Rabbani, M.: A sustainable second-generation biodiesel supply chain network design problem under risk. Omega. 66, 258 (2016)
Bare, J.: TRACI 2.0: the tool for the reduction and assessment of chemical and other environmental impacts 2.0. Clean Techn. Environ. Policy. 13(5), 687–696 (2011)
Benoît, C., Mazijn, B.: Guidelines for Social Life Cycle Assessment of Products. UNEP/SETAC Life Cycle Initiative (2009)
Ben-Tal, A., El Ghaoui, L., Nemirovski, A.: Robust Optimization. Princeton University Press (2009)
Ben-Tal, A., Nemirovski, A.: Robust convex optimization. Math. Oper. Res. 23(4), 769–805 (1998)
Bertsimas, D., Sim, M.: The price of robustness. Oper. Res. 52(1), 35–53 (2004)
Brand, G., Braunschweig, A., Scheidegger, A., Schwank, O.: 1998. Weighting in Ecobalances with the ecoscarcity method–Ecofactors 1997. BUWAL (SAFEL) Environment Series, 297
Brandenburg, M., Govindan, K., Sarkis, J., Seuring, S.: Quantitative models for sustainable supply chain management: developments and directions. Eur. J. Oper. Res. 233(2), 299–312 (2014)
Cardoso, S.R., Barbosa-Póvoa, A.P.F., Relvas, S.: Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty. Eur. J. Oper. Res. 226(3), 436–451 (2013)
Carlsson, C., Fullér, R.: On possibilistic mean value and variance of fuzzy numbers. Fuzzy Sets Syst. 122(2), 315–326 (2001)
Carter, C.R., Jennings, M.M.: Social responsibility and supply chain relationships. Transp. Res. E: Logist. Transp. Rev. 38(1), 37–52 (2002)
Carter, C.R., Rogers, D.S.: A framework of sustainable supply chain management: moving toward new theory. Int. J. Phys. Distrib. Logist. Manag. 38(5), 360–387 (2008)
Chaabane, A., Ramudhin, A., Paquet, M.: Design of sustainable supply chains under the emission trading scheme. Int. J. Prod. Econ. 135(1), 37–49 (2012)
Cruz, J.M.: The impact of corporate social responsibility in supply chain management: multicriteria decision-making approach. Decis. Support. Syst. 48(1), 224–236 (2009)
Cruz, J.M., Wakolbinger, T.: Multiperiod effects of corporate social responsibility on supply chain networks, transaction costs, emissions, and risk. Int. J. Prod. Econ. 116(1), 61–74 (2008)
Daghigh, R., Jabalameli, M., Amiri, A., Pishvaee, M.: A multi-objective location-inventory model for 3PL providers with sustainable considerations under uncertainty. Int. J. Ind. Eng. Comput. 7(4), 615–634 (2016)
Dehghanian, F., Mansour, S.: Designing sustainable recovery network of end-of-life products using genetic algorithm. Resour. Conserv. Recycl. 53(10), 559–570 (2009)
De Rosa, V., Gebhard, M., Hartmann, E., Wollenweber, J.: Robust sustainable bi-directional logistics network design under uncertainty. Int. J. Prod. Econ. 145(1), 184–198 (2013)
Devika, K., Jafarian, A., Nourbakhsh, V.: Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques. Eur. J. Oper. Res. 235(3), 594–615 (2014)
Dubois, D., Fargier, H., Fortemps, P.: Fuzzy scheduling: modelling flexible constraints vs. coping with incomplete knowledge. Eur. J. Oper. Res. 147(2), 231–252 (2003)
Ehrgott, M.: Multicriteria optimization. Springer Science & Business Media (2006)
ETI.: 2009. The Base Code. <http://www.ethicaltrade.org/resources/key-eti-resources/eti-base-code>
Ferretti, I., Zanoni, S., Zavanella, L., Diana, A.: Greening the aluminium supply chain. Int. J. Prod. Econ. 108(1), 236–245 (2007)
FLA.: 2011. Workplace Code of Conduct. <http://www.fairlabor.org>
Fleischmann, M., Van Nunen, J.A., Gräve, B.: Integrating closed-loop supply chains and spare-parts management at IBM. Interfaces. 33(6), 44–56 (2003)
Fonseca, M.C., García-Sánchez, Á., Ortega-Mier, M., Saldanha-da-Gama, F.: A stochastic bi-objective location model for strategic reverse logistics. TOP. 18(1), 158–184 (2010)
Goedkoop, M., Heijungs, R., Huijbregts, M., De Schryver, A., Struijs, J., van Zelm, R.: ReCiPe 2008. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level, 1, (2009)
Goedkoop, M., Spriensma, R.: 2000. The eco-indicator 99: a damage oriented method for life cycle impact assessment-methodology report (available at www. pre. nl)
Goetschalcks, M., Fleischmann, B.: Strategic network design, pp. 117–132. Supply Chain Management and Advanced Planning (2008)
Govindan, K., Jafarian, A., Khodaverdi, R., Devika, K.: Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. Int. J. Prod. Econ. 152, 9–28 (2014)
Govindan, K., Jafarian, A., Nourbakhsh, V.: Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic. Comput. Oper. Res. 62, 112–130 (2015)
GRI.: Sustainability Reporting Guidelines, version 3.1 (2011)
Guinée, J.B., Gorrée, M., Heijungs, R., Huppes, G., Kleijn, R., De Koning, A., Van Oers, L., Wegener Sleeswijk, A., Suh, S., Udo de Haes, H.A., De Bruijn, H.: Life cycle assessment; an operational guide to the ISO standards; parts 1 and 2. In: Ministry of Housing, Spatial Planning and Environment (VROM) and centre of Environmental Science (CML). Den Haag and Leiden, Dordrecht (2001)
Hassini, E., Surti, C., Searcy, C.: A literature review and a case study of sustainable supply chains with a focus on metrics. Int. J. Prod. Econ. 140(1), 69–82 (2012)
Hauschild, M. and Potting, J., 2005. Spatial differentiation in life cycle impact assessment: the EDIP2003 methodology. Environmental news, (80)
Hugo, A., Pistikopoulos, E.N.: Environmentally conscious long-range planning and design of supply chain networks. J. Clean. Prod. 13(15), 1471–1491 (2005)
Hwang, C.L., Masud, A.S.M.: Multiple objective decision making—methods and applications: a state-of-the-art survey, vol. 164. Springer Science & Business Media (2012)
ISO.: 2010. Final Draft International Standard ISO/FDIS 26000:2010(E), Guidance on Social Responsibility
Inuiguchi, M., Ramık, J.: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Sets Syst. 111(1), 3–28 (2000)
Jayaraman, V.: Production planning for closed-loop supply chains with product recovery and reuse: an analytical approach. Int. J. Prod. Res. 44(5), 981–998 (2006)
Jayaraman, V., Guide Jr., V.D.R., Srivastava, R.: A closed-loop logistics model for remanufacturing. J. Oper. Res. Soc. 50(5), 497–508 (1999)
Jiménez, M.: Ranking fuzzy numbers through the comparison of its expected intervals. Int. J. Uncertainty Fuzziness Knowledge-Based Syst. 4(04), 379–388 (1996)
Jolliet, O., Margni, M., Charles, R., Humbert, S., Payet, J., Rebitzer, G., Rosenbaum, R.: IMPACT 2002+: a new life cycle impact assessment methodology. Int. J. Life Cycle Assess. 8(6), 324–330 (2003)
Klibi, W., Martel, A., Guitouni, A.: The design of robust value-creating supply chain networks: a critical review. Eur. J. Oper. Res. 203(2), 283–293 (2010)
Luo, Y., Zhou, M., Caudill, R.J.: An integrated e-supply chain model for agile and environmentally conscious manufacturing. IEEE/ASME Trans. Mechatron. 6(4), 377–386 (2001)
Mohammadi, M., Torabi, S.A., Tavakkoli-Moghaddam, R.: Sustainable hub location under mixed uncertainty. Transp. Res. E Logist. Transp. Rev. 62, 89–115 (2014)
Mota, B., Gomes, M.I., Carvalho, A., Barbosa-Povoa, A.P.: Towards supply chain sustainability: economic, environmental and social design and planning. J. Clean. Prod. 105, 14–27 (2015)
Mula, J., Poler, R., Garcia, J.P.: MRP with flexible constraints: a fuzzy mathematical programming approach. Fuzzy Sets Syst. 157(1), 74–97 (2006)
Mulvey, J.M., Vanderbei, R.J., Zenios, S.A.: Robust optimization of large-scale systems. Oper. Res. 43(2), 264–281 (1995)
Pishvaee, M.S., Farahani, R.Z., Dullaert, W.: A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Comput. Oper. Res. 37(6), 1100–1112 (2010a)
Pishvaee, M.S., Jolai, F., Razmi, J.: A stochastic optimization model for integrated forward/reverse logistics network design. J. Manuf. Syst. 28(4), 107–114 (2009)
Pishvaee, M.S., Kianfar, K., Karimi, B.: Reverse logistics network design using simulated annealing. Int. J. Adv. Manuf. Technol. 47(1–4), 269–281 (2010b)
Pishvaee, M.S., Razmi, J.: Environmental supply chain network design using multi-objective fuzzy mathematical programming. Appl. Math. Model. 36(8), 3433–3446 (2012)
Pishvaee, M.S., Razmi, J., Torabi, S.A.: An accelerated benders decomposition algorithm for sustainable supply chain network design under uncertainty: a case study of medical needle and syringe supply chain. Transp. Res. E Logist. Transp. Rev. 67, 14–38 (2014)
Pishvaee, M.S., Razmi, J., Torabi, S.A.: Robust possibilistic programming for socially responsible supply chain network design: a new approach. Fuzzy Sets Syst. 206, 1–20 (2012a)
Pishvaee, M.S., Torabi, S.A.: A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst. 161(20), 2668–2683 (2010)
Pishvaee, M.S., Torabi, S.A., Razmi, J.: Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty. Comput. Ind. Eng. 62(2), 624–632 (2012b)
Ramezani, M., Kimiagari, A.M., Karimi, B., Hejazi, T.H.: Closed-loop supply chain network design under a fuzzy environment. Knowl.-Based Syst. 59, 108–120 (2014)
Ramudhin, A., Chaabane, A., Kharoune, M., Paquet, M.: Carbon market sensitive green supply chain network design. In: 2008 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1093–1097. IEEE (2008)
Rebitzer, G., Ekvall, T., Frischknecht, R., Hunkeler, D., Norris, G., Rydberg, T., Schmidt, W.P., Suh, S., Weidema, B.P., Pennington, D.W.: Life cycle assessment: part 1: framework, goal and scope definition, inventory analysis, and applications. Environ. Int. 30(5), 701–720 (2004)
Sahinidis, N.V.: Optimization under uncertainty: state-of-the-art and opportunities. Comput. Chem. Eng. 28(6), 971–983 (2004)
SAI: Social Accountability 8000 (SA8000), International Standard. SAI, New York (2008)
Sazvar, Z., Mirzapour Al-e-hashem, S.M.J., Baboli, A., Jokar, M.A.: A bi-objective stochastic programming model for a centralized green supply chain with deteriorating products. Int. J. Prod. Econ. 150, 140–154 (2014)
Seuring, S., Müller, M.: From a literature review to a conceptual framework for sustainable supply chain management. J. Clean. Prod. 16(15), 1699–1710 (2008)
Seuring, S.: A review of modeling approaches for sustainable supply chain management. Decis. Support. Syst. 54(4), 1513–1520 (2013)
Sheu, J.B.: Green supply chain management, reverse logistics and nuclear power generation. Transp. Res. E Logist. Transp. Rev. 44(1), 19–46 (2008)
Sheu, J.B., Chou, Y.H., Hu, C.C.: An integrated logistics operational model for green-supply chain management. Transp. Res. E Logist. Transp. Rev. 41(4), 287–313 (2005)
Soyster, A.L.: Technical note—convex programming with set-inclusive constraints and applications to inexact linear programming. Oper. Res. 21(5), 1154–1157 (1973)
Steen, B.: A systematic approach to environmental priority strategies in product development (EPS): version 2000-general system characteristics, p. 4. Centre for Environmental Assessment of Products and Material Systems, Gothenburg (1999)
Sustainability Assessment and Reporting for the University of Michigan's Ann Arbor Campus, Report No. CSS02–04,.: (2002). Available from: http://css.snre.umich.edu/css_doc/CSS02-04.pdf
Talaei, M., Moghaddam, B.F., Pishvaee, M.S., Bozorgi-Amiri, A., Gholamnejad, S.: A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry. J. Clean. Prod. 113, 662–673 (2016)
Tang, C.S., Zhou, S.: Research advances in environmentally and socially sustainable operations. Eur. J. Oper. Res. 223(3), 585–594 (2012)
Torabi, S.A., Hassini, E.: An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets Syst. 159(2), 193–214 (2008)
Tseng, S.C., Hung, S.W.: A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management. J. Environ. Manag. 133, 315–322 (2014)
UNGC.: 2007. An Inspirational Guide to Implementing the Global Compact. <http://www.unglobalcompact.org/>
Ülkü, M.A.: Dare to care: shipment consolidation reduces not only costs, but also environmental damage. Int. J. Prod. Econ. 139(2), 438–446 (2012)
WCED: Our Common Future. Oxford University Press, Oxford/New York (1987)
World Business Council for Sustainable Development: Corporate Social Responsibility: Meeting Changing Expectations. World Business Council for Sustainable Development (1999)
Zhang, P., Zhang, W.G.: Multiperiod mean absolute deviation fuzzy portfolio selection model with risk control and cardinality constraints. Fuzzy Sets Syst. 255, 74–91 (2014)
Zhang, S., Lee, C.K.M., Wu, K., Choy, K.L.: Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels. Expert Syst. Appl. 65, 87–99 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Daghigh, R., Pishvaee, M.S., Torabi, S.A. (2017). Sustainable Logistics Network Design Under Uncertainty. In: Cinar, D., Gakis, K., Pardalos, P. (eds) Sustainable Logistics and Transportation. Springer Optimization and Its Applications, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-319-69215-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-69215-9_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69214-2
Online ISBN: 978-3-319-69215-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)