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Multi-objective models and real case study for dual-channel FAP supply chain network design with fuzzy information

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Abstract

This paper studies on the dual-channel (the traditional channel and the E-commerce channel) supply chain network design (SCND) for fresh agri-product (FAP) under information uncertainty. The model is to solve the integration network design issues about production, supply, and sales of FAP, as well as to minimize the supply chain operation cost and maximizing the satisfaction degree of the logistics demand between supply chain (SC) nodes simultaneously. First, the triangular-fuzzy-number is used to depict the information uncertainty in the SCND. Then the handling cost of wasted FAP and quantitative traceability cost of FAP are considered in addition to the regular transportation cost and fixed cost for facility location, which makes it more closely and suitable for the real case when compared with the models in existing literatures. Due to there is always a lower and upper bound for delivery time of each logistics demand node in SC in real life. This problem is then formulated as an attenuation function, for depicting the satisfaction degree in each demand node. Afterwards, the multi-objective planning method is utilized to represent the mutual trade-off among supply-chain participants. The proposed models are solved with two-phase method to guarantee the optimality of the solution. Finally, the effectiveness and applicability of the proposed models and algorithm are validated with a real case. The result shows the presented SCND models can guide relevant enterprises to make optimize decisions with fuzzy information.

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References

  • Aung, M. M., & Chang, Y. S. (2014). Traceability in a food supply chain: Safety and quality perspectives. Food Control, 39, 172–184.

    Article  Google Scholar 

  • Ayağ, Z., Samanlioglu, F., & Büyüközkan, G. (2013). A fuzzy QFD approach to determine supply chain management strategies in the dairy industry. Journal of Intelligent Manufacturing, 24(5), 1111–1122.

    Google Scholar 

  • Ballou, R. H. (1968). Dynamic warehouse location analysis. Journal of Marketing Research (JMR), 5(3), 271–276.

    Article  Google Scholar 

  • Berman, O., Krass, D., & Drezner, Z. (2003). The gradual covering decay location problem on a network. European Journal of Operational Research, 151(3), 474–480.

    Article  Google Scholar 

  • Berman, O., & Wang, J. (2004). Probabilistic location problems with discrete demand weights. Networks, 44(1), 47–57.

    Article  Google Scholar 

  • Berman, O., & Wang, J. (2008). The probabilistic 1-maximal covering problem on a network with discrete demand weights. Journal of the Operational Research Society, 59(10), 1398–1405.

    Article  Google Scholar 

  • Bosona, T., & Gebresenbet, G. (2013). Food traceability as an integral part of logistics management in food and agricultural supply chain. Food Control, 33(1), 32–48.

    Article  Google Scholar 

  • Chern, C.-C., Lei, S.-T., & Huang, K.-L. (2014). Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multi-commodity supply chain network. Journal of Intelligent Manufacturing, 25(1), 1–25.

    Article  Google Scholar 

  • Gan, M., & Lin, W.-H. (Eds.) (2010). The effect of demand representation on locating facilities in a supply chain network. In 2010 IEEE international conference on service operations and logistics and informatics (SOLI). IEEE.

  • Gan, M., Chen, S., & Yan, Y. (2013). The effect of roadway capacity expansion on facility sitting. Applied Mathematics & Information Sciences, 7(2L), 575–581.

    Article  Google Scholar 

  • Gan, M., Li, Z., & Chen, S. (2014). On the transformation mechanism for formulate a multi-product two-layer supply chain network design problem as a network flow model. Mathematical Problems in Engineering, 2014, 480127. doi:10.1155/2014/480127.

  • Gustavsson, J., Cederberg, C., Sonesson, U., Van Otterdijk, R., & Meybeck, A. (2011). Global food losses and food waste. Rome: Food and Agriculture Organization of the United Nations.

    Google Scholar 

  • Hiremath, N. C., Sahu, S., & Tiwari, M. K. (2013). Multi objective outbound logistics network design for a manufacturing supply chain. Journal of Intelligent Manufacturing, 24(6), 1071–1084.

    Article  Google Scholar 

  • Jouzdani, J., Sadjadi, S. J., & Fathian, M. (2013). Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case of Tehran. Applied Mathematical Modelling. doi:10.1016/j.apm.

  • Lai, Y.-J., & Hwang, C.-L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49(2), 121–133.

    Article  Google Scholar 

  • Liang, T.-F. (2008). Integrating production-transportation planning decision with fuzzy multiple goals in supply chains. International Journal of Production Research, 46(6), 1477–1494.

    Article  Google Scholar 

  • Liang, C.-J., Chen, M., Gen, M., & Jo, J. (2014). A multi-objective genetic algorithm for yard crane scheduling problem with multiple work lines. Journal of Intelligent Manufacturing, 25(5), 1013–1024.

    Article  Google Scholar 

  • Liao, S.-H., Hsieh, C.-L., & Lai, P.-J. (2011). An evolutionary approach for multi-objective optimization of the integrated location-inventory distribution network problem in vendor-managed inventory. Expert Systems with Applications, 38(6), 67–76.

    Google Scholar 

  • Li, X., Zhang, B., & Li, H. (2006). Computing efficient solutions to fuzzy multiple objective linear programming problems. Fuzzy Sets and Systems, 157(10), 1328–1332.

    Article  Google Scholar 

  • Manzini, R., & Bindi, F. (2009). Strategic design and operational management optimization of a multi stage physical distribution system. Transportation Research Part E: Logistics and Transportation Review, 45(6), 915–936.

    Article  Google Scholar 

  • Mohammadi Bidhandi, H., Mohd Yusuff, R., Megat Ahmad, M. M. H., & Abu Bakar, M. R. (2009). Development of a new approach for deterministic supply chain network design. European Journal of Operational Research, 198(1), 121–128.

    Article  Google Scholar 

  • Nagurney, A., Masoumi, A. H., & Yu, M. (2012). Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 9(2), 205–231.

    Article  Google Scholar 

  • Paksoy, T., Pehlivan, N. Y., & Özceylan, E. (2012). Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer. Applied Mathematical Modelling, 36(6), 2762–2776.

    Article  Google Scholar 

  • Rui, L. I. (2010). The distribution and consideration of chinese agriculture product. Modern Economic Information, 16, 180.

    Google Scholar 

  • Stanley Lee, E., & Li, R. J. (1993). Fuzzy multiple objective programming and compromise programming with Pareto optimum. Fuzzy Sets and Systems, 53(3), 275–288.

    Article  Google Scholar 

  • Talluri, S., & Baker, R. (2002). A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3), 544–558.

    Article  Google Scholar 

  • Wang, C.-H., & Tsai, S.-W. (2013). Optimizing bi-objective imperfect preventive maintenance model for series-parallel system using established hybrid genetic algorithm. Journal of Intelligent Manufacturing, 25(3), 603–616.

    Article  Google Scholar 

  • Widodo, K., Nagasawa, H., Morizawa, K., & Ota, M. (2006). A periodical flowering-harvesting model for delivering agricultural fresh products. European Journal of Operational Research, 170(1), 24–43.

    Article  Google Scholar 

  • Yang, L., Deuse, J., & Jiang, P. (2013). Multi-objective optimization of facility planning for energy intensive companies. Journal of Intelligent Manufacturing, 24(6), 1095–1109.

    Article  Google Scholar 

  • Yu, M., & Nagurney, A. (2013). Competitive food supply chain networks with application to fresh produce. European Journal of Operational Research, 224(2), 273–282.

    Article  Google Scholar 

  • Zhao, D., Wang, Y., Sheng, S., & Lin, Z. (2014). Multi-objective optimal design of small scale resistance spot welding process with principal component analysis and response surface methodology. Journal of Intelligent Manufacturing, 25(6), 1335–1348.

    Article  Google Scholar 

  • Zimmermann, H.-J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1(1), 45–55.

    Article  Google Scholar 

Download references

Acknowledgments

The work is supported by the Nature Science Foundation of China (Grant No. 71403225) Fundamental Research Funds for the Central Universities (Grant No. SWJTU12CX114). And the Soft science foundation of Sichuan province STA of China (Grant Nos. 2014ZR0019 and 2015ZR0141) and Sichuan province cyclic economy research program (Grant No. XHJJ-1411).

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Authors and Affiliations

  1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China

    Juan Yu, Mi Gan, Shaoquan Ni & Dingjun Chen

  2. Department of business, Zhengzhou Chenggong University of Finance and Economics, Zhengzhou, 451200, China

    Juan Yu

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  1. Juan Yu
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  2. Mi Gan
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Correspondence to Mi Gan, Shaoquan Ni or Dingjun Chen.

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Yu, J., Gan, M., Ni, S. et al. Multi-objective models and real case study for dual-channel FAP supply chain network design with fuzzy information. J Intell Manuf 29, 389–403 (2018). https://doi.org/10.1007/s10845-015-1115-8

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  • DOI: https://doi.org/10.1007/s10845-015-1115-8

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