Abstract
In order to better cope with the problem of material procurement, this paper establishes a multi-objective optimization model in a systematic analysis framework for material procurement considering supply risk. This paper firstly combs and identifies the influencing factors of supply risk, and constructs a supply risk evaluation system from the dimensions of quality, price, delivery, service and technology. Secondly, based on the linguistic scale and fuzzy theory, this paper measures the supply risk of the candidate suppliers, and estimates the relevant parameters of the multi-objective optimization model by using the triangular fuzzy numbers. In addition, traditional intelligent algorithms are easily falling into a local optimal solution when solving programming problems. Through numerical simulation experiments, it is verified that the optimization model established in this paper can effectively simulate the operation of the enterprise in actual business. At the same time, the proposed model is feasible and useful for the selection of candidate suppliers and the portfolio optimization of material procurement.
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References
Cunha AL, Santos MO, Morabito R, Barbosa-Póvoa A (2018) An integrated approach for production lot sizing and raw material purchasing. Eur J Oper Res 269:923–938
Lee AHI, Kang H-Y, Lai C-M, Hong W-Y (2013) An integrated model for lot sizing with supplier selection and quantity discounts. Appl Math Model 37:4733–4746
Srai JS, Lorentz H (2019) Developing design principles for the digitalisation of purchasing and supply management. J Purch Supply Manag 25:78–98
Xu X, Hao J, Deng Y, Wang Y (2017) Design optimization of resource combination for collaborative logistics network under uncertainty. Appl Soft Comput 560(7):684–691
Kellner F, Lienland B, Utz S (2019) An a posteriori decision support methodology for solving the multi-criteria supplier selection problem. Eur J Oper Res 272:505–522
Xu X, Sun Y (2020) Optimization of task-route matching based on multi-hub and spoke collaborative logistics network. Chin J Manage Sci 27(9):175–182 (In Chinese)
Li J, Sun X, Wang F, Wu D (2014a) Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach. Ann Oper Res 234:57–76
Kolotzek C, Helbig C, Thorenz A, Reller A, Tuma A (2018) A company-oriented model for the assessment of raw material supply risks, environmental impact and social implications. J Clean Prod 176:566–580
Kumar A, Jain V, Kumar S (2014) A comprehensive environment friendly approach for supplier selection. Omega Int J Manag Sci 42:109–123
Vilko JPP, Hallikas JM (2012) Risk assessment in multimodal supply chains. Int J Prod Econ 140:586–595
Behzadi G, O’Sullivan MJ, Olsen TL, Zhang A (2018) Agribusiness supply chain risk management: a review of quantitative decision models. Omega 79:21–42
Achzet B, Helbig C (2013) How to evaluate raw material supply risks—an overview. Resour Policy 38:435–447
Liao H, Xu Z, Zeng X-J (2015) Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Trans Fuzzy Syst 23:1343–1355
Acknowledgements
This work was supported by National Natural Science Foundation of China (No. 71771206, 71425002, and 71571179) and President’s Youth Foundation of the Institutes of Science and Development, CAS (Y7X111Q01).
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Hao, J., Li, J., Wu, D., Sun, X. (2020). Portfolio Optimization of Material Purchasing Considering Supply Risk . In: Li, X., Xu, X. (eds) Proceedings of the Seventh International Forum on Decision Sciences. Uncertainty and Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-15-5720-0_4
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DOI: https://doi.org/10.1007/978-981-15-5720-0_4
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