A robust bi-objective uncertain green supply chain network management
Abstract
Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function considers minimization of supply chain costs while the second objective function minimizes CO2 emission level. Conditional Value at Risk (CVaR) approach is used to deal with demand uncertainty in compliance with data driven approach, employed to deal with the stochastic level of CO2 emission. The implementation of the proposed model has been demonstrated using some randomly selected numbers and the results are analyzed accordingly.
References
Ait-Kadi, D., & Abdulnour, G. (2013). Green Closed-Loop Supply Chain Network Design: A Literature Review. International Journal of Operations and Logistics Management.
Bertsimas, D., & Brown, D. B. (2009). Constructing uncertainty sets for robust linear optimization. Operations Research, 57(6), 1483-1495.
Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299-312.
Chibeles-Martins, N., Pinto-Varela, T., Barbosa-Póvoa, A. P., & Novais, A. Q. (2016). A multi-objective meta-heuristic approach for the design and planning of green supply chains-MBSA. Expert Systems with Applications, 47, 71-84.
Coskun, S., Ozgur, L., Polat, O., & Gungor, A. (2016). A model proposal for green supply chain network design based on consumer segmentation. Journal of Cleaner Production, 110, 149-157.
Dotoli, M., Epicoco, N., & Falagario, M. (2015). A Technique for Supply Chain Network Design under Uncertainty using Cross-Efficiency Fuzzy Data Envelopment Analysis. IFAC-PapersOnLine, 48(3), 634-639.
Dwyer, J. (2013). Transformation for sustainable agriculture: what role for the second Pillar of CAP? Bio-based and Applied Economics, 2(1), 29-47.
Eskandarpour, M., Dejax, P., Miemczyk, J., & Péton, O. (2015). Sustainable supply chain network design: An optimization-oriented review. Omega, 54, 11-32.
Feng, Z., Wang, Z., & Chen, Y. (2014). The equilibrium of closed-loop supply chain supernetwork with time-dependent parameters. Transportation Research Part E: Logistics and Transportation Review, 64, 1-11.
Garg, K., Kannan, D., Diabat, A., & Jha, P. (2015). A multi-criteria optimization approach to manage environmental issues in closed loop supply chain network design. Journal of Cleaner Production, 100, 297-314.
Golpîra, H., Zandieh, M., Najafi, E., & Sadi-Nezhad, S. (2015). Coordination of green supply chain network, considering uncertain demand and stochastic CO2 emission level. Journal of Industrial Engineering and Management Studies, 2(2), 11.
Golpîra, H., Zandieh, M., Najafi, E., & Sadi-Nezhad, S. (In Press). A multi-objective multi-echelon green supply chain network design problem with risk-averse retailers in an uncertain environment. Scientia Iranica: Transaction on Industrial Engineering.
Gui-tao, Z., Hao, S., & Jin-song, H. (2014). Research on supply chain network equilibrium problem with multi-type suppliers. Paper presented at the Service Systems and Service Management (ICSSSM), 2014 11th International Conference on.
Gunasekaran, A., Subramanian, N., & Rahman, S. (2015). Green supply chain collaboration and incentives: Current trends and future directions. Transportation Research Part E: Logistics and Transportation Review, 74, 1-10.
Jamshidi, R., Ghomi, S. F., & Karimi, B. (2012). Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method. Scientia Iranica, 19(6), 1876-1886.
Kagawa, S., Suh, S., Hubacek, K., Wiedmann, T., Nansai, K., & Minx, J. (2015). CO 2 emission clusters within global supply chain networks: Implications for climate change mitigation. Global Environmental Change, 35, 486-496.
Kannegiesser, M., Günther, H.-O., & Autenrieb, N. (2015). The time-to-sustainability optimization strategy for sustainable supply network design. Journal of Cleaner Production, 108, 451-463.
Kawasaki, T., Yamada, T., Itsubo, N., & Inoue, M. (2015). Multi Criteria Simulation Model for Lead Times, Costs and CO2 Emissions in a Low-carbon Supply Chain Network. Procedia CIRP, 26, 329-334.
Li, B., Chen, P., Li, Q., & Wang, W. (2014). Dual-channel supply chain pricing decisions with a risk-averse retailer. International Journal of Production Research, 52(23), 7132-7147.
Mallidis, I., Vlachos, D., Iakovou, E., & Dekker, R. (2014). Design and planning for green global supply chains under periodic review replenishment policies. Transportation Research Part E: Logistics and Transportation Review, 72, 210-235.
Martí, J. M. C., Tancrez, J.-S., & Seifert, R. W. (2015). Carbon footprint and responsiveness trade-offs in supply chain network design. International Journal of Production Economics, 166, 129-142.
Miret, C., Chazara, P., Montastruc, L., Negny, S., & Domenech, S. (2016). Design of bioethanol green supply chain: Comparison between first and second generation biomass concerning economic, environmental and social criteria. Computers & Chemical Engineering, 85, 16-35.
Mulvey, J. M., Vanderbei, R. J., & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations research, 43(2), 264-281.
Nakamichi, K., Hanaoka, S., & Kawahara, Y. (2016). Estimation of cost and CO 2 emissions with a sustainable cross-border supply chain in the automobile industry: A case study of Thailand and neighboring countries. Transportation Research Part D: Transport and Environment, 43, 158-168.
Natarajan, K., Pachamanova, D., & Sim, M. (2009). Constructing risk measures from uncertainty sets. Operations research, 57(5), 1129-1141.
Nouira, I., Hammami, R., Frein, Y., & Temponi, C. (2016). Design of forward supply chains: Impact of a carbon emissions-sensitive demand. International Journal of Production Economics, 173, 80-98.
Rezaee, A., Dehghanian, F., Fahimnia, B., & Beamon, B. (2015). Green supply chain network design with stochastic demand and carbon price. Annals of Operations Research, 1-23.
Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513-1520.
Sharifzadeh, M., Garcia, M. C., & Shah, N. (2015). Supply chain network design and operation: Systematic decision-making for centralized, distributed, and mobile biofuel production using mixed integer linear programming (MILP) under uncertainty. Biomass and Bioenergy, 81, 401-414.
Soleimani, H., & Kannan, G. (2015). A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks. Applied Mathematical Modelling, 39(14), 3990-4012.
Talaei, M., Moghaddam, B. F., Pishvaee, M. S., Bozorgi-Amiri, A., & Gholamnejad, S. (2015). A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry. Journal of Cleaner Production.
Urata, T., Yamada, T., Itsubo, N., & Inoue, M. (2015). Modeling and Balancing for Costs and CO 2 Emissions in Global Supply Chain Network among Asian Countries. Procedia CIRP, 26, 664-669.
Wu, K.-J., Liao, C.-J., Tseng, M.-L., & Chiu, A. S. (2015). Exploring decisive factors in green supply chain practices under uncertainty. International Journal of Production Economics, 159, 147-157.
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