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Designing a bio-fuel network considering links reliability and risk-pooling effect in bio-refineries

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  • Salimi, F.
  • Vahdani, Behnam

Abstract

Bio-fuel is one of the most important alternatives to fossil fuels due to energy shortages. The bio-fuel is derived from biomass that is obtained from agricultural products such as plant debris. In addition, the supply chain is affected by risks which are due to several reasons such as economic, natural phenomena, political and etc. The occurrence of such events can cause disruption in supply chain which can significantly increase the total supply chain costs and also prevent serve to customers. Reliability is involved the capability of a network to achieve an anticipated process such as ``communication". Analysis of network reliability has acknowledged significant consideration and is consequently broadly studied to forecast and avoid any network failure. In order to distribute bio-fuel to the customers, designing a reliable and sustainable bio-fuel supply chain is very importance. Thus a growth in bio-fuel production demonstrates the requirement for establishing an effective and reliable network of chain that not only accomplishes sound under regular circumstances nevertheless restricted risk under various unanticipated disruption situations. This paper presents mathematical model to design an efficient bio-fuel supply chain network at pre-disaster stage that considering failure in the connecting links between the facilities. In which the probability of failure of the links is forecasted by a spatial statistic approach and also due to the fact that disasters can cause disruptions in bio-refineries, leads to use the risk-pooling effect in order to reduce total costs. In order to solve the proposed mathematical model, two meta-heuristic algorithms containing genetic algorithm (GA) and bat algorithm (BA) are utilized. The results show that by increasing the reliability and improvement of connecting links between facilities and considering the risk-pooling effect on disrupted bio-refineries, the total costs of supply chain can be considerably reduced.

Suggested Citation

  • Salimi, F. & Vahdani, Behnam, 2018. "Designing a bio-fuel network considering links reliability and risk-pooling effect in bio-refineries," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 96-107.
    • Handle: RePEc:eee:reensy:v:174:y:2018:i:c:p:96-107
    DOI: 10.1016/j.ress.2018.02.020
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    References listed on IDEAS

    as
    1. Huang, Yongxi & Chen, Chien-Wei & Fan, Yueyue, 2010. "Multistage optimization of the supply chains of biofuels," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 820-830, November.
    2. Yun Bai & Xiaopeng Li & Fan Peng & Xin Wang & Yanfeng Ouyang, 2015. "Effects of Disruption Risks on Biorefinery Location Design," Energies, MDPI, vol. 8(2), pages 1-19, February.
    3. Tingting Cui & Yanfeng Ouyang & Zuo-Jun Max Shen, 2010. "Reliable Facility Location Design Under the Risk of Disruptions," Operations Research, INFORMS, vol. 58(4-part-1), pages 998-1011, August.
    4. Wang, Xin & Lim, Michael K. & Ouyang, Yanfeng, 2015. "Infrastructure deployment under uncertainties and competition: The biofuel industry case," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 1-15.
    5. Lian Qi & Zuo-Jun Max Shen & Lawrence V. Snyder, 2010. "The Effect of Supply Disruptions on Supply Chain Design Decisions," Transportation Science, INFORMS, vol. 44(2), pages 274-289, May.
    6. Vahdani, Behnam & Tavakkoli-Moghaddam, Reza & Modarres, Mohammad & Baboli, Armand, 2012. "Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1152-1168.
    7. Sohn, Jungyul, 2006. "Evaluating the significance of highway network links under the flood damage: An accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 491-506, July.
    8. Marufuzzaman, Mohammad & Eksioglu, Sandra D. & Li, Xiaopeng & Wang, Jin, 2014. "Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 122-145.
    9. Zhang, Ying & Snyder, Lawrence V. & Qi, Mingyao & Miao, Lixin, 2016. "A heterogeneous reliable location model with risk pooling under supply disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 151-178.
    10. Bana e Costa, Carlos A. & Oliveira, Carlos S. & Vieira, Victor, 2008. "Prioritization of bridges and tunnels in earthquake risk mitigation using multicriteria decision analysis: Application to Lisbon," Omega, Elsevier, vol. 36(3), pages 442-450, June.
    11. Selvik, Jon Tømmerås & Signoret, Jean-Pierre, 2017. "How to interpret safety critical failures in risk and reliability assessments," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 61-68.
    12. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    13. Mark Daskin & Collette Coullard & Zuo-Jun Shen, 2002. "An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results," Annals of Operations Research, Springer, vol. 110(1), pages 83-106, February.
    14. Fiondella, Lance & Lin, Yi-Kuei & Pham, Hoang & Chang, Ping-Chen & Li, Chendong, 2017. "A confidence-based approach to reliability design considering correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 102-114.
    15. Li, Xiaopeng & Ouyang, Yanfeng, 2010. "A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 535-548, May.
    16. Mohammadi, M. & Dehbari, S. & Vahdani, Behnam, 2014. "Design of a bi-objective reliable healthcare network with finite capacity queue under service covering uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 15-41.
    17. Chen, Chien-Wei & Fan, Yueyue, 2012. "Bioethanol supply chain system planning under supply and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 150-164.
    18. Vahdani, Behnam & Mohammadi, M., 2015. "A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 67-87.
    19. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    20. Zuo-Jun Max Shen & Roger Lezhou Zhan & Jiawei Zhang, 2011. "The Reliable Facility Location Problem: Formulations, Heuristics, and Approximation Algorithms," INFORMS Journal on Computing, INFORMS, vol. 23(3), pages 470-482, August.
    21. Gonzales, Daniela & Searcy, Erin M. & Ekşioğlu, Sandra D., 2013. "Cost analysis for high-volume and long-haul transportation of densified biomass feedstock," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 48-61.
    22. Ren, Jingzheng & An, Da & Liang, Hanwei & Dong, Liang & Gao, Zhiqiu & Geng, Yong & Zhu, Qinghua & Song, Shaoxian & Zhao, Wenhui, 2016. "Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties," Energy, Elsevier, vol. 103(C), pages 151-166.
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