Portfolio optimisation of material purchase considering supply risk – A multi-objective programming model
For the sake of better coping with the problem of material procurement, a multi-objective optimisation model was established in a systematic analysis framework for material procurement considering supply risk. First, this paper combs and identifies supply risk factors and constructs a supply risk ev...
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| Published in: | International journal of production economics Vol. 230; p. 107803 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.12.2020
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| ISSN: | 0925-5273, 1873-7579 |
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| Abstract | For the sake of better coping with the problem of material procurement, a multi-objective optimisation model was established in a systematic analysis framework for material procurement considering supply risk. First, this paper combs and identifies supply risk factors and constructs a supply risk evaluation system from the dimensions of quality, price, delivery, service and technology. Second, based on the linguistic scale and fuzzy theory, this paper measures the supply risk of candidate suppliers and estimates the relevant parameters of the multi-objective optimisation model by using the triangular fuzzy numbers. In addition, an improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized in this paper to solve the multi-objective model, since traditional intelligent algorithms have slow convergence speed and are easily trapping into local optimisation. Finally, this paper conducts simulation experiments by setting three types of decision-makers with different risk preferences and provides material procurement combination schemes in different scenarios. Through numerical simulation experiments, it was verified that the optimisation model established in this paper was feasible and useful for the selection of candidate suppliers and the portfolio optimisation of material procurement. |
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| AbstractList | For the sake of better coping with the problem of material procurement, a multi-objective optimisation model was established in a systematic analysis framework for material procurement considering supply risk. First, this paper combs and identifies supply risk factors and constructs a supply risk evaluation system from the dimensions of quality, price, delivery, service and technology. Second, based on the linguistic scale and fuzzy theory, this paper measures the supply risk of candidate suppliers and estimates the relevant parameters of the multi-objective optimisation model by using the triangular fuzzy numbers. In addition, an improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized in this paper to solve the multi-objective model, since traditional intelligent algorithms have slow convergence speed and are easily trapping into local optimisation. Finally, this paper conducts simulation experiments by setting three types of decision-makers with different risk preferences and provides material procurement combination schemes in different scenarios. Through numerical simulation experiments, it was verified that the optimisation model established in this paper was feasible and useful for the selection of candidate suppliers and the portfolio optimisation of material procurement. |
| ArticleNumber | 107803 |
| Author | Sun, Xiaolei Li, Jianping Wu, Dengsheng Hao, Jun |
| Author_xml | – sequence: 1 givenname: Jun surname: Hao fullname: Hao, Jun email: haojun181@mails.ucas.ac.cn organization: Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China – sequence: 2 givenname: Jianping surname: Li fullname: Li, Jianping email: ljp@casipm.ac.cn organization: Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China – sequence: 3 givenname: Dengsheng surname: Wu fullname: Wu, Dengsheng email: wds@casipm.ac.cn organization: Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China – sequence: 4 givenname: Xiaolei surname: Sun fullname: Sun, Xiaolei email: xlsun@casipm.ac.cn organization: Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China |
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